Class SatParameters.Builder
java.lang.Object
com.google.protobuf.AbstractMessageLite.Builder
com.google.protobuf.AbstractMessage.Builder<SatParameters.Builder>
com.google.protobuf.GeneratedMessage.Builder<SatParameters.Builder>
com.google.ortools.sat.SatParameters.Builder
- All Implemented Interfaces:
SatParametersOrBuilder, com.google.protobuf.Message.Builder, com.google.protobuf.MessageLite.Builder, com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder, Cloneable
- Enclosing class:
SatParameters
public static final class SatParameters.Builder
extends com.google.protobuf.GeneratedMessage.Builder<SatParameters.Builder>
implements SatParametersOrBuilder
Contains the definitions for all the sat algorithm parameters and their default values. NEXT TAG: 356Protobuf type
operations_research.sat.SatParameters-
Method Summary
Modifier and TypeMethodDescriptionaddAllExtraSubsolvers(Iterable<String> values) A convenient way to add more workers types.addAllFilterSubsolvers(Iterable<String> values) repeated string filter_subsolvers = 293;addAllIgnoreSubsolvers(Iterable<String> values) Rather than fully specifying subsolvers, it is often convenient to just remove the ones that are not useful on a given problem or only keep specific ones for testing.addAllRestartAlgorithms(Iterable<? extends SatParameters.RestartAlgorithm> values) The restart strategies will change each time the strategy_counter is increased.addAllSubsolverParams(Iterable<? extends SatParameters> values) It is possible to specify additional subsolver configuration.addAllSubsolvers(Iterable<String> values) In multi-thread, the solver can be mainly seen as a portfolio of solvers with different parameters.addExtraSubsolvers(String value) A convenient way to add more workers types.addExtraSubsolversBytes(com.google.protobuf.ByteString value) A convenient way to add more workers types.addFilterSubsolvers(String value) repeated string filter_subsolvers = 293;addFilterSubsolversBytes(com.google.protobuf.ByteString value) repeated string filter_subsolvers = 293;addIgnoreSubsolvers(String value) Rather than fully specifying subsolvers, it is often convenient to just remove the ones that are not useful on a given problem or only keep specific ones for testing.addIgnoreSubsolversBytes(com.google.protobuf.ByteString value) Rather than fully specifying subsolvers, it is often convenient to just remove the ones that are not useful on a given problem or only keep specific ones for testing.The restart strategies will change each time the strategy_counter is increased.addSubsolverParams(int index, SatParameters value) It is possible to specify additional subsolver configuration.addSubsolverParams(int index, SatParameters.Builder builderForValue) It is possible to specify additional subsolver configuration.addSubsolverParams(SatParameters value) It is possible to specify additional subsolver configuration.addSubsolverParams(SatParameters.Builder builderForValue) It is possible to specify additional subsolver configuration.It is possible to specify additional subsolver configuration.addSubsolverParamsBuilder(int index) It is possible to specify additional subsolver configuration.addSubsolvers(String value) In multi-thread, the solver can be mainly seen as a portfolio of solvers with different parameters.addSubsolversBytes(com.google.protobuf.ByteString value) In multi-thread, the solver can be mainly seen as a portfolio of solvers with different parameters.build()clear()Stop the search when the gap between the best feasible objective (O) and our best objective bound (B) is smaller than a limit.Whether we generate and add Chvatal-Gomory cuts to the LP at root node.Whether we generate clique cuts from the binary implication graph.For the lin max constraints, generates the cuts described in "Strong mixed-integer programming formulations for trained neural networks" by Ross Anderson et.If true, we start by an empty LP, and only add constraints not satisfied by the current LP solution batch by batch.Whether we generate MIR cuts at root node.When the LP objective is fractional, do we add the cut that forces the linear objective expression to be greater or equal to this fractional value rounded up?Whether we generate RLT cuts.Whether we generate Zero-Half cuts at root node.When this is true, then the variables that appear in any of the reason of the variables in a conflict have their activity bumped.In order to not get stuck in local optima, when this is non-zero, we try to also work on "older" solutions with a worse objective value so we get a chance to follow a different LS/LNS trajectory.All at_most_one constraints with a size <= param will be replaced by a quadratic number of binary implications.If true, then the precedences propagator try to detect for each variable if it has a set of "optional incoming arc" for which at least one of them is present.optional .operations_research.sat.SatParameters.BinaryMinizationAlgorithm binary_minimization_algorithm = 34 [default = BINARY_MINIMIZATION_FROM_UIP_AND_DECISIONS];If non-negative, perform a binary search on the objective variable in order to find an [min, max] interval outside of which the solver proved unsat/sat under this amount of conflict.optional double blocking_restart_multiplier = 66 [default = 1.4];optional int32 blocking_restart_window_size = 65 [default = 5000];A non-negative level indicating how much we should try to fully encode Integer variables as Boolean.Indicates if the CP-SAT layer should catch Control-C (SIGINT) signals when calling solve.If true, and if the problem is UNSAT, a DRAT proof of this UNSAT property is checked after the solver has finished.If true, inferred clauses are checked with an LRAT checker as they are learned, in presolve (reduced to trivial simplifications if cp_model_presolve is false), and in each worker.If true, and if output_lrat_proof is true and the problem is UNSAT, check that the merged proof file is valid, i.e., that clause sharing between workers is correct.If chronological backtracking is enabled, this is the minimum number of conflicts before we will consider backjumping.Clause activity parameters (same effect as the one on the variables).All the clauses with a LBD (literal blocks distance) lower or equal to this parameters will always be kept.All the clause with a LBD lower or equal to this will be kept except if its activity hasn't been bumped in the last 32 cleanup phase.All the clause with a LBD lower or equal to this will be kept except if its activity hasn't been bumped since the previous cleanup phase.optional .operations_research.sat.SatParameters.ClauseOrdering clause_cleanup_ordering = 60 [default = CLAUSE_ACTIVITY];Trigger a cleanup when this number of "deletable" clauses is learned.Increase clause_cleanup_period by this amount after each cleanup.During a cleanup, if clause_cleanup_target is 0, we will delete the clause_cleanup_ratio of "deletable" clauses instead of aiming for a fixed target of clauses to keep.During a cleanup, we will always keep that number of "deletable" clauses.Temporary flag util the feature is more mature.If positive, we spend some effort on each core: - At level 1, we use a simple heuristic to try to minimize an UNSAT core. - At level 2, we use propagation to minimize the core but also identify literal in at most one relationship in this core.Whether or not the assumption levels are taken into account during the LBD computation.If true, when the max-sat algo find a core, we compute the minimal number of literals in the core that needs to be true to have a feasible solution.Whether we presolve the cp_model before solving it.How much effort do we spend on probing. 0 disables it completely.Whether we also use the sat presolve when cp_model_presolve is true.If true, and during integer conflict resolution (icr) the 1-UIP is an integer literal for which we do not have an associated Boolean.optional double cut_active_count_decay = 156 [default = 0.8];Target number of constraints to remove during cleanup.Control the global cut effort.These parameters are similar to sat clause management activity parameters.Crash if the LRAT UNSAT proof is invalid.Crash if presolve breaks a feasible hint.Crash if we do not manage to complete the hint into a full solution.If positive, try to stop just after that many presolve rules have been applied.We have two different postsolve code.Try even more subsumption options during conflict analysis.optional string default_restart_algorithms = 70 [default = "LUBY_RESTART,LBD_MOVING_AVERAGE_RESTART,DL_MOVING_AVERAGE_RESTART"];Infer products of Boolean or of Boolean time IntegerVariable from the linear constrainst in the problem.If true, we detect variable that are unique to a table constraint and only there to encode a cost on each tuple.If true, it disable all constraint expansion.If true, registers more lns subsolvers with different parameters.If >=0, each time we have a conflict, we try to subsume the last n learned clause with it.Linear constraint with a complex right hand side (more than a single interval) need to be expanded, there is a couple of way to do that.Encore cumulative with fixed demands and capacity as a reservoir constraint.Whether we enumerate all solutions of a problem without objective.If true, expand all_different constraints that are not permutations.If true, expand the reservoir constraints by creating booleans for all possible precedences between event and encoding the constraint.Mainly useful for testing.If true and the Lp relaxation of the problem has a solution, try to exploit it.optional bool exploit_all_precedences = 220 [default = false];When branching on a variable, follow the last best solution value.If true and the Lp relaxation of the problem has an integer optimal solution, try to exploit it.When branching an a variable that directly affect the objective, branch on the value that lead to the best objective first.When branching on a variable, follow the last best relaxation solution value.A convenient way to add more workers types.It is possible that "intermediate" clauses during conflict resolution subsumes some of the clauses that propagated.How much dtime for each LS batch.On each restart, we randomly choose if we use decay (with this parameter) or no decay.When stagnating, feasibility jump will either restart from a default solution (with some possible randomization), or randomly pertubate the current solution.How much do we linearize the problem in the local search code.Maximum size of no_overlap or no_overlap_2d constraint for a quadratic expansion.This is a factor that directly influence the work before each restart.Max distance between the default value and the pertubated value relative to the range of the domain of the variable.Probability for a variable to have a non default value upon restarts or perturbations.If true, the final response addition_solutions field will be filled with all solutions from our solutions pool.If true, add information about the derived variable domains to the CpSolverResponse.Internal parameter.repeated string filter_subsolvers = 293;Try to find large "rectangle" in the linear constraint matrix with identical lines.By propagating (or just using binary clauses), one can detect that all literal of a clause are actually in at most one relationship.Whether we try to find more independent cores for a given set of assumptions in the core based max-SAT algorithms.If true, variables appearing in the solution hints will be fixed to their hinted value.optional .operations_research.sat.SatParameters.FPRoundingMethod fp_rounding = 165 [default = PROPAGATION_ASSISTED];optional double glucose_decay_increment = 23 [default = 0.01];optional int32 glucose_decay_increment_period = 24 [default = 5000];The activity starts at 0.8 and increment by 0.01 every 5000 conflicts until 0.95.Conflict limit used in the phase that exploit the solution hint.If true, we don't keep names in our internal copy of the user given model.Rather than fully specifying subsolvers, it is often convenient to just remove the ones that are not useful on a given problem or only keep specific ones for testing.Run a max-clique code amongst all the x !optional .operations_research.sat.SatParameters.Polarity initial_polarity = 2 [default = POLARITY_FALSE];The initial value of the variables activity.Proportion of deterministic time we should spend on inprocessing.Parameters for an heuristic similar to the one described in "An effective learnt clause minimization approach for CDCL Sat Solvers", https://www.ijcai.org/proceedings/2017/0098.pdf This is the amount of dtime we should spend on this technique during each inprocessing phase.optional bool inprocessing_minimization_use_all_orderings = 298 [default = false];optional bool inprocessing_minimization_use_conflict_analysis = 297 [default = true];The amount of dtime we should spend on probing for each inprocessing round.Whether we use the algorithm described in "Clausal Congruence closure", Armin Biere, Katalin Fazekas, Mathias Fleury, Nils Froleyks, 2024.Whether we use the SAT sweeping algorithm described in "Clausal Equivalence Sweeping", Armin Biere, Katalin Fazekas, Mathias Fleury, Nils Froleyks, 2025.If true, the solver will add a default integer branching strategy to the already defined search strategy.optional int32 interleave_batch_size = 134 [default = 0];Experimental.If true, we disable the presolve reductions that remove feasible solutions from the search space.Experimental.Only use lb-relax if we have at least that many workers.A non-negative level indicating the type of constraints we consider in the LP relaxation.Linear constraints that are not pseudo-Boolean and that are longer than this size will be split into sqrt(size) intermediate sums in order to have faster propation in the CP engine.optional double lns_initial_deterministic_limit = 308 [default = 0.1];Initial parameters for neighborhood generation.If we try to load at most ones and exactly ones constraints when running the pure SAT presolve.Add a prefix to all logs.Whether the solver should log the search progress.Whether the solver should display per sub-solver search statistics.Log to response proto.Log to stdout.optional double lp_dual_tolerance = 267 [default = 1e-07];The internal LP tolerances used by CP-SAT.Cut generator for all diffs can add too many cuts for large all_diff constraints.Max domain size for all_different constraints to be expanded.If chronological backtracking is enabled, this is the maximum number of levels we will backjump over, otherwise we will backtrack.optional double max_clause_activity_value = 18 [default = 1e+20];If a constraint/cut in LP is not active for that many consecutive OPTIMAL solves, remove it from the LP.Max number of time we perform cut generation and resolve the LP at level 0.Maximum time allowed in deterministic time to solve a problem.Max domain size for expanding linear2 constraints (ax + by ==/!When loading a*x + b*y ==/!The maximum time allowed to check the DRAT proof (this can take more time than the solve itself).Detects when the space where items of a no_overlap_2d constraint can placed is disjoint (ie., fixed boxes split the domain).In the integer rounding procedure used for MIR and Gomory cut, the maximum "scaling" we use (must be positive).If the number of expressions in the lin_max is less that the max size parameter, model expansion replaces target = max(xi) by linear constraint with the introduction of new booleans bi such that bi => target == xi.Maximum memory allowed for the whole thread containing the solver.Maximum number of conflicts allowed to solve a problem.The limit on the number of cuts in our cut pool.Stops after that number of batches has been scheduled.Max number of intervals for the timetable_edge_finding algorithm to propagate.If the number of pairs to look is below this threshold, do an extra step of propagation in the no_overlap_2d constraint by looking at all pairs of intervals.In case of large reduction in a presolve iteration, we perform multiple presolve iterations.optional .operations_research.sat.SatParameters.MaxSatAssumptionOrder max_sat_assumption_order = 51 [default = DEFAULT_ASSUMPTION_ORDER];If true, adds the assumption in the reverse order of the one defined by max_sat_assumption_order.optional .operations_research.sat.SatParameters.MaxSatStratificationAlgorithm max_sat_stratification = 53 [default = STRATIFICATION_DESCENT];Create one literal for each disjunction of two pairs of tasks.Maximum time allowed in seconds to solve a problem.optional double max_variable_activity_value = 16 [default = 1e+100];optional double merge_at_most_one_work_limit = 146 [default = 100000000];During presolve, we use a maximum clique heuristic to merge together no-overlap constraints or at most one constraints.optional .operations_research.sat.SatParameters.ConflictMinimizationAlgorithm minimization_algorithm = 4 [default = RECURSIVE];A different algorithm during PB resolution.Minimize and detect subsumption of shared clauses immediately after they are imported.While adding constraints, skip the constraints which have orthogonality less than 'min_orthogonality_for_lp_constraints' with already added constraints during current call.If true, some continuous variable might be automatically scaled.As explained in mip_precision and mip_max_activity_exponent, we cannot always reach the wanted precision during scaling.Even if we make big error when scaling the objective, we can always derive a correct lower bound on the original objective by using the exact lower bound on the scaled integer version of the objective.Any value in the input mip with a magnitude lower than this will be set to zero.To avoid integer overflow, we always force the maximum possible constraint activity (and objective value) according to the initial variable domain to be smaller than 2 to this given power.We need to bound the maximum magnitude of the variables for CP-SAT, and that is the bound we use.Any finite values in the input MIP must be below this threshold, otherwise the model will be reported invalid.When solving a MIP, we do some basic floating point presolving before scaling the problem to integer to be handled by CP-SAT.If this is false, then mip_var_scaling is only applied to variables with "small" domain.By default, any variable/constraint bound with a finite value and a magnitude greater than the mip_max_valid_magnitude will result with a invalid model.All continuous variable of the problem will be multiplied by this factor.When scaling constraint with double coefficients to integer coefficients, we will multiply by a power of 2 and round the coefficients.In some context, like in a portfolio of search, it makes sense to name a given parameters set for logging purpose.Add that many lazy constraints (or cuts) at once in the LP.The new linear propagation code treat all constraints at once and use an adaptation of Bellman-Ford-Tarjan to propagate constraint in a smarter order and potentially detect propagation cycle earlier.If less than this number of boxes are present in a no-overlap 2d, we create 4 Booleans per pair of boxes: - Box 2 is after Box 1 on x. - Box 1 is after Box 2 on x. - Box 2 is after Box 1 on y. - Box 1 is after Box 2 on y.After each restart, if the number of conflict since the last strategy change is greater that this, then we increment a "strategy_counter" that can be use to change the search strategy used by the following restarts.We distinguish subsolvers that consume a full thread, and the ones that are always interleaved.optional int32 num_search_workers = 100 [default = 0];This will create incomplete subsolvers (that are not LNS subsolvers) that use the feasibility jump code to find improving solution, treating the objective improvement as a hard constraint.Specify the number of parallel workers (i.e. threads) to use during search.For the cut that can be generated at any level, this control if we only try to generate them at the root node.If one try to solve a MIP model with CP-SAT, because we assume all variable to be integer after scaling, we will not necessarily have the correct optimal.The default optimization method is a simple "linear scan", each time trying to find a better solution than the previous one.Do a more conventional tree search (by opposition to SAT based one) where we keep all the explored node in a tree.This has no effect if optimize_with_core is false.If true, a DRAT proof that all the clauses inferred by the solver are valid is output to a file.If true, an LRAT proof that all the clauses inferred by the solver are valid is output to several files (one for presolve -- reduced to trivial simplifications if cp_model_presolve is false, one per worker, and one for the merged proof).Same as for the clauses, but for the learned pseudo-Boolean constraints.optional double pb_cleanup_ratio = 47 [default = 0.5];optional bool permute_presolve_constraint_order = 179 [default = false];This is mainly here to test the solver variability.If true and we have first solution LS workers, tries in some phase to follow a LS solutions that violates has litle constraints as possible.If non-zero, then we change the polarity heuristic after that many number of conflicts in an arithmetically increasing fashion.Whether we try to do a few degenerate iteration at the end of an LP solve to minimize the fractionality of the integer variable in the basis.optional .operations_research.sat.SatParameters.VariableOrder preferred_variable_order = 1 [default = IN_ORDER];Whether we use an heuristic to detect some basic case of blocked clause in the SAT presolve.Apply Bounded Variable Addition (BVA) if the number of clauses is reduced by stricly more than this threshold.During presolve, we apply BVE only if this weight times the number of clauses plus the number of clause literals is not increased.During presolve, only try to perform the bounded variable elimination (BVE) of a variable x if the number of occurrences of x times the number of occurrences of not(x) is not greater than this parameter.If true, we will extract from linear constraints, enforcement literals of the form "integer variable at bound => simplified constraint".A few presolve operations involve detecting constraints included in other constraint.optional double presolve_probing_deterministic_time_limit = 57 [default = 30];How much substitution (also called free variable aggregation in MIP litterature) should we perform at presolve.Whether or not we use Bounded Variable Addition (BVA) in the presolve.The maximum "deterministic" time limit to spend in probing.How many combinations of pairs or triplets of variables we want to scan.Some search decisions might cause a really large number of propagations to happen when integer variables with large domains are only reduced by 1 at each step.The solver ignores the pseudo costs of variables with number of recordings less than this threshold.Experimental code: specify if the objective pushes all tasks toward the start of the schedule.A number between 0 and 1 that indicates the proportion of branching variables that are selected randomly instead of choosing the first variable from the given variable_ordering strategy.Randomize fixed search.The proportion of polarity chosen at random.At the beginning of each solve, the random number generator used in some part of the solver is reinitialized to this seed.optional double relative_gap_limit = 160 [default = 0];If cp_model_presolve is true and there is a large proportion of fixed variable after the first model copy, remap all the model to a dense set of variable before the full presolve even starts.If true, the solver tries to repair the solution given in the hint.The restart strategies will change each time the strategy_counter is increased.In the moving average restart algorithms, a restart is triggered if the window average times this ratio is greater that the global average.optional double restart_lbd_average_ratio = 71 [default = 1];Restart period for the FIXED_RESTART strategy.Size of the window for the moving average restarts.Even at the root node, we do not want to spend too much time on the LP if it is "difficult".The amount of "effort" to spend in dynamic programming for computing routing cuts.If the length of an infeasible path is less than this value, a cut will be added to exclude it.If the size of a subset of nodes of a RoutesConstraint is less than this value, use linear constraints of size 1 and 2 (such as capacity and time window constraints) enforced by the arc literals to compute cuts for this subset (unless the subset size is less than routing_cut_subset_size_for_tight_binary_relation_bound, in which case the corresponding algorithm is used instead).Similar to above, but with an even stronger algorithm in O(n!).Similar to routing_cut_subset_size_for_exact_binary_relation_bound but use a bound based on shortest path distances (which respect triangular inequality).Similar to above, but with a different algorithm producing better cuts, at the price of a higher O(2^n) complexity, where n is the subset size.Experimental.optional .operations_research.sat.SatParameters.SearchBranching search_branching = 82 [default = AUTOMATIC_SEARCH];Search randomization will collect the top 'search_random_variable_pool_size' valued variables, and pick one randomly.Allows sharing of new learned binary clause between workers.How much deeper compared to the ideal max depth of the tree is considered "balanced" enough to still accept a split.In order to limit total shared memory and communication overhead, limit the total number of nodes that may be generated in the shared tree.Enables shared tree search.How many open leaf nodes should the shared tree maintain per worker.How much dtime a worker will wait between proposing splits.optional .operations_research.sat.SatParameters.SharedTreeSplitStrategy shared_tree_split_strategy = 239 [default = SPLIT_STRATEGY_AUTO];If true, shared tree workers share their target phase when returning an assigned subtree for the next worker to use.If true, workers share more of the information from their local trail.Minimum restarts before a worker will replace a subtree that looks "bad" based on the average LBD of learned clauses.Allows sharing of short glue clauses between workers.The amount of dtime between each export of shared glue clauses.Allows sharing of the bounds of modified variables at level 0.Allows sharing of the bounds on linear2 discovered at level 0.Allows objective sharing between workers.Add a shaving phase (where the solver tries to prove that the lower or upper bound of a variable are infeasible) to the probing searchSpecifies the amount of deterministic time spent of each try at shaving a bound in the shaving search.Specifies the threshold between two modes in the shaving procedure.If solution_pool_size is <= this, we will use DP to keep a "diverse" set of solutions (the one further apart via hamming distance) in the pool.Size of the top-n different solutions kept by the solver.For an optimization problem, stop the solver as soon as we have a solution.Mainly used when improving the presolver.optional bool stop_after_root_propagation = 252 [default = false];The parameter num_conflicts_before_strategy_changes is increased by that much after each strategy change.It is possible to specify additional subsolver configuration.In multi-thread, the solver can be mainly seen as a portfolio of solvers with different parameters.If we remove clause that we now are "implied" by others.At a really low cost, during the 1-UIP conflict computation, it is easy to detect if some of the involved reasons are subsumed by the current conflict.Deterministic time limit for symmetry detection.Whether we try to automatically detect the symmetries in a model and exploit them.How much we try to "compress" a table constraint.At root level, we might compute the transitive closure of "precedences" relations so that we can exploit that in scheduling problems.optional bool use_absl_random = 180 [default = false];Turn on extra propagation for the circuit constraint.When this is true, the no_overlap_2d constraint is reinforced with an energetic reasoning that uses an area-based energy.Block a moving restart algorithm if the trail size of the current conflict is greater than the multiplier times the moving average of the trail size at the previous conflicts.If true, try to backtrack as little as possible on conflict and re-imply the clauses later.This can be beneficial if there is a lot of no-overlap constraints but a relatively low number of different intervals in the problem.Enable a heuristic to solve cumulative constraints using a modified energy constraint.When this is true, the cumulative constraint is reinforced with propagators from the disjunctive constraint to improve the inference on a set of tasks that are disjunctive at the root of the problem.When set, it activates a few scheduling parameters to improve the lower bound of scheduling problems.optional bool use_dynamic_precedence_in_cumulative = 268 [default = false];Whether we try to branch on decision "interval A before interval B" rather than on intervals bounds.When this is true, the no_overlap_2d constraint is reinforced with energetic reasoning.Whether we use the ERWA (Exponential Recency Weighted Average) heuristic as described in "Learning Rate Based Branching Heuristic for SAT solvers", J.H.Liang, V.The solver usually exploit the LP relaxation of a model.Use extended probing (probe bool_or, at_most_one, exactly_one).Parameters for an heuristic similar to the one described in the paper: "Feasibility Jump: an LP-free Lagrangian MIP heuristic", Bjørnar Luteberget, Giorgio Sartor, 2023, Mathematical Programming Computation.Adds a feasibility pump subsolver along with lns subsolvers.If true, detect and create constraint for integer variable that are "after" a set of intervals in the same cumulative constraint.Stores and exploits "implied-bounds" in the solver.Turns on neighborhood generator based on local branching LP.When set, this activates a propagator for the no_overlap_2d constraint that uses any eventual linear constraints of the model in the form `{start interval 1} - {end interval 2} + c*w <= ub` to detect that two intervals must overlap in one dimension for some values of `w`.Testing parameters used to disable all lns workers.Experimental parameters to disable everything but lns.Disable every other type of subsolver, setting this turns CP-SAT into a pure local-search solver.This should be better on integer problems.If true, search will search in ascending max objective value (when minimizing) starting from the lower bound of the objective.This search differs from the previous search as it will not use assumptions to bound the objective, and it will recreate a full model with the hardcoded objective value.For an optimization problem, whether we follow some hints in order to find a better first solution.If true, we automatically detect variables whose constraint are always enforced by the same literal and we mark them as optional.When this is true, the cumulative constraint is reinforced with overload checking, i.e., an additional level of reasoning based on energy.Experimental.If this is true, then the polarity of a variable will be the last value it was assigned to, or its default polarity if it was never assigned since the call to ResetDecisionHeuristic().When this is true, then a disjunctive constraint will try to use the precedence relations between time intervals to propagate their bounds further.If true, search will continuously probe Boolean variables, and integer variable bounds.Turns on relaxation induced neighborhood generator.Enable or disable "inprocessing" which is some SAT presolving done at each restart to the root level.Set on shared subtree workers.Enable stronger and more expensive propagation on no_overlap constraint.When we have symmetry, it is possible to "fold" all variables from the same orbit into a single variable, while having the same power of LP relaxation.When this is true, the cumulative constraint is reinforced with timetable edge finding, i.e., an additional level of reasoning based on the conjunction of energy and mandatory parts.When this is true, the no_overlap_2d constraint is reinforced with propagators from the cumulative constraints.optional bool use_try_edge_reasoning_in_no_overlap_2d = 299 [default = false];Each time a conflict is found, the activities of some variables are increased by one.This search takes all Boolean or integer variables, and maximize or minimize them in order to reduce their domain. -1 is automatic, otherwise value 0 disables it, and 1, 2, or 3 changes something.Probability of using compound move search each restart.How long violation_ls should wait before perturbating a solution.doubleStop the search when the gap between the best feasible objective (O) and our best objective bound (B) is smaller than a limit.booleanWhether we generate and add Chvatal-Gomory cuts to the LP at root node.booleanWhether we generate clique cuts from the binary implication graph.booleanFor the lin max constraints, generates the cuts described in "Strong mixed-integer programming formulations for trained neural networks" by Ross Anderson et.booleanIf true, we start by an empty LP, and only add constraints not satisfied by the current LP solution batch by batch.booleanWhether we generate MIR cuts at root node.booleanWhen the LP objective is fractional, do we add the cut that forces the linear objective expression to be greater or equal to this fractional value rounded up?booleanWhether we generate RLT cuts.booleanWhether we generate Zero-Half cuts at root node.booleanWhen this is true, then the variables that appear in any of the reason of the variables in a conflict have their activity bumped.intIn order to not get stuck in local optima, when this is non-zero, we try to also work on "older" solutions with a worse objective value so we get a chance to follow a different LS/LNS trajectory.intAll at_most_one constraints with a size <= param will be replaced by a quadratic number of binary implications.booleanIf true, then the precedences propagator try to detect for each variable if it has a set of "optional incoming arc" for which at least one of them is present.optional .operations_research.sat.SatParameters.BinaryMinizationAlgorithm binary_minimization_algorithm = 34 [default = BINARY_MINIMIZATION_FROM_UIP_AND_DECISIONS];intIf non-negative, perform a binary search on the objective variable in order to find an [min, max] interval outside of which the solver proved unsat/sat under this amount of conflict.doubleoptional double blocking_restart_multiplier = 66 [default = 1.4];intoptional int32 blocking_restart_window_size = 65 [default = 5000];intA non-negative level indicating how much we should try to fully encode Integer variables as Boolean.booleanIndicates if the CP-SAT layer should catch Control-C (SIGINT) signals when calling solve.booleanIf true, and if the problem is UNSAT, a DRAT proof of this UNSAT property is checked after the solver has finished.booleanIf true, inferred clauses are checked with an LRAT checker as they are learned, in presolve (reduced to trivial simplifications if cp_model_presolve is false), and in each worker.booleanIf true, and if output_lrat_proof is true and the problem is UNSAT, check that the merged proof file is valid, i.e., that clause sharing between workers is correct.intIf chronological backtracking is enabled, this is the minimum number of conflicts before we will consider backjumping.doubleClause activity parameters (same effect as the one on the variables).intAll the clauses with a LBD (literal blocks distance) lower or equal to this parameters will always be kept.intAll the clause with a LBD lower or equal to this will be kept except if its activity hasn't been bumped in the last 32 cleanup phase.intAll the clause with a LBD lower or equal to this will be kept except if its activity hasn't been bumped since the previous cleanup phase.optional .operations_research.sat.SatParameters.ClauseOrdering clause_cleanup_ordering = 60 [default = CLAUSE_ACTIVITY];intTrigger a cleanup when this number of "deletable" clauses is learned.intIncrease clause_cleanup_period by this amount after each cleanup.doubleDuring a cleanup, if clause_cleanup_target is 0, we will delete the clause_cleanup_ratio of "deletable" clauses instead of aiming for a fixed target of clauses to keep.intDuring a cleanup, we will always keep that number of "deletable" clauses.booleanTemporary flag util the feature is more mature.intIf positive, we spend some effort on each core: - At level 1, we use a simple heuristic to try to minimize an UNSAT core. - At level 2, we use propagation to minimize the core but also identify literal in at most one relationship in this core.booleanWhether or not the assumption levels are taken into account during the LBD computation.booleanIf true, when the max-sat algo find a core, we compute the minimal number of literals in the core that needs to be true to have a feasible solution.booleanWhether we presolve the cp_model before solving it.intHow much effort do we spend on probing. 0 disables it completely.booleanWhether we also use the sat presolve when cp_model_presolve is true.booleanIf true, and during integer conflict resolution (icr) the 1-UIP is an integer literal for which we do not have an associated Boolean.doubleoptional double cut_active_count_decay = 156 [default = 0.8];intTarget number of constraints to remove during cleanup.intControl the global cut effort.doubleThese parameters are similar to sat clause management activity parameters.booleanCrash if the LRAT UNSAT proof is invalid.booleanCrash if presolve breaks a feasible hint.booleanCrash if we do not manage to complete the hint into a full solution.intIf positive, try to stop just after that many presolve rules have been applied.booleanWe have two different postsolve code.booleanTry even more subsumption options during conflict analysis.optional string default_restart_algorithms = 70 [default = "LUBY_RESTART,LBD_MOVING_AVERAGE_RESTART,DL_MOVING_AVERAGE_RESTART"];com.google.protobuf.ByteStringoptional string default_restart_algorithms = 70 [default = "LUBY_RESTART,LBD_MOVING_AVERAGE_RESTART,DL_MOVING_AVERAGE_RESTART"];static final com.google.protobuf.Descriptors.Descriptorcom.google.protobuf.Descriptors.DescriptorbooleanInfer products of Boolean or of Boolean time IntegerVariable from the linear constrainst in the problem.booleanIf true, we detect variable that are unique to a table constraint and only there to encode a cost on each tuple.booleanIf true, it disable all constraint expansion.booleanIf true, registers more lns subsolvers with different parameters.intIf >=0, each time we have a conflict, we try to subsume the last n learned clause with it.booleanLinear constraint with a complex right hand side (more than a single interval) need to be expanded, there is a couple of way to do that.booleanEncore cumulative with fixed demands and capacity as a reservoir constraint.booleanWhether we enumerate all solutions of a problem without objective.booleanIf true, expand all_different constraints that are not permutations.booleanIf true, expand the reservoir constraints by creating booleans for all possible precedences between event and encoding the constraint.booleanMainly useful for testing.booleanIf true and the Lp relaxation of the problem has a solution, try to exploit it.booleanoptional bool exploit_all_precedences = 220 [default = false];booleanWhen branching on a variable, follow the last best solution value.booleanIf true and the Lp relaxation of the problem has an integer optimal solution, try to exploit it.booleanWhen branching an a variable that directly affect the objective, branch on the value that lead to the best objective first.booleanWhen branching on a variable, follow the last best relaxation solution value.getExtraSubsolvers(int index) A convenient way to add more workers types.com.google.protobuf.ByteStringgetExtraSubsolversBytes(int index) A convenient way to add more workers types.intA convenient way to add more workers types.com.google.protobuf.ProtocolStringListA convenient way to add more workers types.booleanIt is possible that "intermediate" clauses during conflict resolution subsumes some of the clauses that propagated.doubleHow much dtime for each LS batch.doubleOn each restart, we randomly choose if we use decay (with this parameter) or no decay.booleanWhen stagnating, feasibility jump will either restart from a default solution (with some possible randomization), or randomly pertubate the current solution.intHow much do we linearize the problem in the local search code.intMaximum size of no_overlap or no_overlap_2d constraint for a quadratic expansion.intThis is a factor that directly influence the work before each restart.doubleMax distance between the default value and the pertubated value relative to the range of the domain of the variable.doubleProbability for a variable to have a non default value upon restarts or perturbations.booleanIf true, the final response addition_solutions field will be filled with all solutions from our solutions pool.booleanIf true, add information about the derived variable domains to the CpSolverResponse.booleanInternal parameter.getFilterSubsolvers(int index) repeated string filter_subsolvers = 293;com.google.protobuf.ByteStringgetFilterSubsolversBytes(int index) repeated string filter_subsolvers = 293;intrepeated string filter_subsolvers = 293;com.google.protobuf.ProtocolStringListrepeated string filter_subsolvers = 293;booleanTry to find large "rectangle" in the linear constraint matrix with identical lines.booleanBy propagating (or just using binary clauses), one can detect that all literal of a clause are actually in at most one relationship.booleanWhether we try to find more independent cores for a given set of assumptions in the core based max-SAT algorithms.booleanIf true, variables appearing in the solution hints will be fixed to their hinted value.optional .operations_research.sat.SatParameters.FPRoundingMethod fp_rounding = 165 [default = PROPAGATION_ASSISTED];doubleoptional double glucose_decay_increment = 23 [default = 0.01];intoptional int32 glucose_decay_increment_period = 24 [default = 5000];doubleThe activity starts at 0.8 and increment by 0.01 every 5000 conflicts until 0.95.intConflict limit used in the phase that exploit the solution hint.booleanIf true, we don't keep names in our internal copy of the user given model.getIgnoreSubsolvers(int index) Rather than fully specifying subsolvers, it is often convenient to just remove the ones that are not useful on a given problem or only keep specific ones for testing.com.google.protobuf.ByteStringgetIgnoreSubsolversBytes(int index) Rather than fully specifying subsolvers, it is often convenient to just remove the ones that are not useful on a given problem or only keep specific ones for testing.intRather than fully specifying subsolvers, it is often convenient to just remove the ones that are not useful on a given problem or only keep specific ones for testing.com.google.protobuf.ProtocolStringListRather than fully specifying subsolvers, it is often convenient to just remove the ones that are not useful on a given problem or only keep specific ones for testing.booleanRun a max-clique code amongst all the x !optional .operations_research.sat.SatParameters.Polarity initial_polarity = 2 [default = POLARITY_FALSE];doubleThe initial value of the variables activity.doubleProportion of deterministic time we should spend on inprocessing.doubleParameters for an heuristic similar to the one described in "An effective learnt clause minimization approach for CDCL Sat Solvers", https://www.ijcai.org/proceedings/2017/0098.pdf This is the amount of dtime we should spend on this technique during each inprocessing phase.booleanoptional bool inprocessing_minimization_use_all_orderings = 298 [default = false];booleanoptional bool inprocessing_minimization_use_conflict_analysis = 297 [default = true];doubleThe amount of dtime we should spend on probing for each inprocessing round.booleanWhether we use the algorithm described in "Clausal Congruence closure", Armin Biere, Katalin Fazekas, Mathias Fleury, Nils Froleyks, 2024.booleanWhether we use the SAT sweeping algorithm described in "Clausal Equivalence Sweeping", Armin Biere, Katalin Fazekas, Mathias Fleury, Nils Froleyks, 2025.booleanIf true, the solver will add a default integer branching strategy to the already defined search strategy.intoptional int32 interleave_batch_size = 134 [default = 0];booleanExperimental.booleanIf true, we disable the presolve reductions that remove feasible solutions from the search space.booleanExperimental.intOnly use lb-relax if we have at least that many workers.intA non-negative level indicating the type of constraints we consider in the LP relaxation.intLinear constraints that are not pseudo-Boolean and that are longer than this size will be split into sqrt(size) intermediate sums in order to have faster propation in the CP engine.doubleoptional double lns_initial_deterministic_limit = 308 [default = 0.1];doubleInitial parameters for neighborhood generation.booleanIf we try to load at most ones and exactly ones constraints when running the pure SAT presolve.Add a prefix to all logs.com.google.protobuf.ByteStringAdd a prefix to all logs.booleanWhether the solver should log the search progress.booleanWhether the solver should display per sub-solver search statistics.booleanLog to response proto.booleanLog to stdout.doubleoptional double lp_dual_tolerance = 267 [default = 1e-07];doubleThe internal LP tolerances used by CP-SAT.intCut generator for all diffs can add too many cuts for large all_diff constraints.intMax domain size for all_different constraints to be expanded.intIf chronological backtracking is enabled, this is the maximum number of levels we will backjump over, otherwise we will backtrack.doubleoptional double max_clause_activity_value = 18 [default = 1e+20];intIf a constraint/cut in LP is not active for that many consecutive OPTIMAL solves, remove it from the LP.intMax number of time we perform cut generation and resolve the LP at level 0.doubleMaximum time allowed in deterministic time to solve a problem.intMax domain size for expanding linear2 constraints (ax + by ==/!intWhen loading a*x + b*y ==/!doubleThe maximum time allowed to check the DRAT proof (this can take more time than the solve itself).intDetects when the space where items of a no_overlap_2d constraint can placed is disjoint (ie., fixed boxes split the domain).intIn the integer rounding procedure used for MIR and Gomory cut, the maximum "scaling" we use (must be positive).intIf the number of expressions in the lin_max is less that the max size parameter, model expansion replaces target = max(xi) by linear constraint with the introduction of new booleans bi such that bi => target == xi.longMaximum memory allowed for the whole thread containing the solver.longMaximum number of conflicts allowed to solve a problem.intThe limit on the number of cuts in our cut pool.intStops after that number of batches has been scheduled.intMax number of intervals for the timetable_edge_finding algorithm to propagate.intIf the number of pairs to look is below this threshold, do an extra step of propagation in the no_overlap_2d constraint by looking at all pairs of intervals.intIn case of large reduction in a presolve iteration, we perform multiple presolve iterations.optional .operations_research.sat.SatParameters.MaxSatAssumptionOrder max_sat_assumption_order = 51 [default = DEFAULT_ASSUMPTION_ORDER];booleanIf true, adds the assumption in the reverse order of the one defined by max_sat_assumption_order.optional .operations_research.sat.SatParameters.MaxSatStratificationAlgorithm max_sat_stratification = 53 [default = STRATIFICATION_DESCENT];intCreate one literal for each disjunction of two pairs of tasks.doubleMaximum time allowed in seconds to solve a problem.doubleoptional double max_variable_activity_value = 16 [default = 1e+100];doubleoptional double merge_at_most_one_work_limit = 146 [default = 100000000];doubleDuring presolve, we use a maximum clique heuristic to merge together no-overlap constraints or at most one constraints.optional .operations_research.sat.SatParameters.ConflictMinimizationAlgorithm minimization_algorithm = 4 [default = RECURSIVE];booleanA different algorithm during PB resolution.booleanMinimize and detect subsumption of shared clauses immediately after they are imported.doubleWhile adding constraints, skip the constraints which have orthogonality less than 'min_orthogonality_for_lp_constraints' with already added constraints during current call.booleanIf true, some continuous variable might be automatically scaled.doubleAs explained in mip_precision and mip_max_activity_exponent, we cannot always reach the wanted precision during scaling.booleanEven if we make big error when scaling the objective, we can always derive a correct lower bound on the original objective by using the exact lower bound on the scaled integer version of the objective.doubleAny value in the input mip with a magnitude lower than this will be set to zero.intTo avoid integer overflow, we always force the maximum possible constraint activity (and objective value) according to the initial variable domain to be smaller than 2 to this given power.doubleWe need to bound the maximum magnitude of the variables for CP-SAT, and that is the bound we use.doubleAny finite values in the input MIP must be below this threshold, otherwise the model will be reported invalid.intWhen solving a MIP, we do some basic floating point presolving before scaling the problem to integer to be handled by CP-SAT.booleanIf this is false, then mip_var_scaling is only applied to variables with "small" domain.booleanBy default, any variable/constraint bound with a finite value and a magnitude greater than the mip_max_valid_magnitude will result with a invalid model.doubleAll continuous variable of the problem will be multiplied by this factor.doubleWhen scaling constraint with double coefficients to integer coefficients, we will multiply by a power of 2 and round the coefficients.getName()In some context, like in a portfolio of search, it makes sense to name a given parameters set for logging purpose.com.google.protobuf.ByteStringIn some context, like in a portfolio of search, it makes sense to name a given parameters set for logging purpose.intAdd that many lazy constraints (or cuts) at once in the LP.booleanThe new linear propagation code treat all constraints at once and use an adaptation of Bellman-Ford-Tarjan to propagate constraint in a smarter order and potentially detect propagation cycle earlier.intIf less than this number of boxes are present in a no-overlap 2d, we create 4 Booleans per pair of boxes: - Box 2 is after Box 1 on x. - Box 1 is after Box 2 on x. - Box 2 is after Box 1 on y. - Box 1 is after Box 2 on y.intAfter each restart, if the number of conflict since the last strategy change is greater that this, then we increment a "strategy_counter" that can be use to change the search strategy used by the following restarts.intWe distinguish subsolvers that consume a full thread, and the ones that are always interleaved.intoptional int32 num_search_workers = 100 [default = 0];intThis will create incomplete subsolvers (that are not LNS subsolvers) that use the feasibility jump code to find improving solution, treating the objective improvement as a hard constraint.intSpecify the number of parallel workers (i.e. threads) to use during search.booleanFor the cut that can be generated at any level, this control if we only try to generate them at the root node.booleanIf one try to solve a MIP model with CP-SAT, because we assume all variable to be integer after scaling, we will not necessarily have the correct optimal.booleanThe default optimization method is a simple "linear scan", each time trying to find a better solution than the previous one.booleanDo a more conventional tree search (by opposition to SAT based one) where we keep all the explored node in a tree.booleanThis has no effect if optimize_with_core is false.booleanIf true, a DRAT proof that all the clauses inferred by the solver are valid is output to a file.booleanIf true, an LRAT proof that all the clauses inferred by the solver are valid is output to several files (one for presolve -- reduced to trivial simplifications if cp_model_presolve is false, one per worker, and one for the merged proof).intSame as for the clauses, but for the learned pseudo-Boolean constraints.doubleoptional double pb_cleanup_ratio = 47 [default = 0.5];booleanoptional bool permute_presolve_constraint_order = 179 [default = false];booleanThis is mainly here to test the solver variability.booleanIf true and we have first solution LS workers, tries in some phase to follow a LS solutions that violates has litle constraints as possible.intIf non-zero, then we change the polarity heuristic after that many number of conflicts in an arithmetically increasing fashion.booleanWhether we try to do a few degenerate iteration at the end of an LP solve to minimize the fractionality of the integer variable in the basis.optional .operations_research.sat.SatParameters.VariableOrder preferred_variable_order = 1 [default = IN_ORDER];booleanWhether we use an heuristic to detect some basic case of blocked clause in the SAT presolve.intApply Bounded Variable Addition (BVA) if the number of clauses is reduced by stricly more than this threshold.intDuring presolve, we apply BVE only if this weight times the number of clauses plus the number of clause literals is not increased.intDuring presolve, only try to perform the bounded variable elimination (BVE) of a variable x if the number of occurrences of x times the number of occurrences of not(x) is not greater than this parameter.booleanIf true, we will extract from linear constraints, enforcement literals of the form "integer variable at bound => simplified constraint".longA few presolve operations involve detecting constraints included in other constraint.doubleoptional double presolve_probing_deterministic_time_limit = 57 [default = 30];intHow much substitution (also called free variable aggregation in MIP litterature) should we perform at presolve.booleanWhether or not we use Bounded Variable Addition (BVA) in the presolve.doubleThe maximum "deterministic" time limit to spend in probing.intHow many combinations of pairs or triplets of variables we want to scan.doubleSome search decisions might cause a really large number of propagations to happen when integer variables with large domains are only reduced by 1 at each step.longThe solver ignores the pseudo costs of variables with number of recordings less than this threshold.booleanExperimental code: specify if the objective pushes all tasks toward the start of the schedule.doubleA number between 0 and 1 that indicates the proportion of branching variables that are selected randomly instead of choosing the first variable from the given variable_ordering strategy.booleanRandomize fixed search.doubleThe proportion of polarity chosen at random.intAt the beginning of each solve, the random number generator used in some part of the solver is reinitialized to this seed.doubleoptional double relative_gap_limit = 160 [default = 0];booleanIf cp_model_presolve is true and there is a large proportion of fixed variable after the first model copy, remap all the model to a dense set of variable before the full presolve even starts.booleanIf true, the solver tries to repair the solution given in the hint.getRestartAlgorithms(int index) The restart strategies will change each time the strategy_counter is increased.intThe restart strategies will change each time the strategy_counter is increased.The restart strategies will change each time the strategy_counter is increased.doubleIn the moving average restart algorithms, a restart is triggered if the window average times this ratio is greater that the global average.doubleoptional double restart_lbd_average_ratio = 71 [default = 1];intRestart period for the FIXED_RESTART strategy.intSize of the window for the moving average restarts.intEven at the root node, we do not want to spend too much time on the LP if it is "difficult".doubleThe amount of "effort" to spend in dynamic programming for computing routing cuts.intIf the length of an infeasible path is less than this value, a cut will be added to exclude it.intIf the size of a subset of nodes of a RoutesConstraint is less than this value, use linear constraints of size 1 and 2 (such as capacity and time window constraints) enforced by the arc literals to compute cuts for this subset (unless the subset size is less than routing_cut_subset_size_for_tight_binary_relation_bound, in which case the corresponding algorithm is used instead).intSimilar to above, but with an even stronger algorithm in O(n!).intSimilar to routing_cut_subset_size_for_exact_binary_relation_bound but use a bound based on shortest path distances (which respect triangular inequality).intSimilar to above, but with a different algorithm producing better cuts, at the price of a higher O(2^n) complexity, where n is the subset size.booleanExperimental.optional .operations_research.sat.SatParameters.SearchBranching search_branching = 82 [default = AUTOMATIC_SEARCH];longSearch randomization will collect the top 'search_random_variable_pool_size' valued variables, and pick one randomly.booleanAllows sharing of new learned binary clause between workers.intHow much deeper compared to the ideal max depth of the tree is considered "balanced" enough to still accept a split.intIn order to limit total shared memory and communication overhead, limit the total number of nodes that may be generated in the shared tree.intEnables shared tree search.doubleHow many open leaf nodes should the shared tree maintain per worker.doubleHow much dtime a worker will wait between proposing splits.optional .operations_research.sat.SatParameters.SharedTreeSplitStrategy shared_tree_split_strategy = 239 [default = SPLIT_STRATEGY_AUTO];booleanIf true, shared tree workers share their target phase when returning an assigned subtree for the next worker to use.booleanIf true, workers share more of the information from their local trail.intMinimum restarts before a worker will replace a subtree that looks "bad" based on the average LBD of learned clauses.booleanAllows sharing of short glue clauses between workers.doubleThe amount of dtime between each export of shared glue clauses.booleanAllows sharing of the bounds of modified variables at level 0.booleanAllows sharing of the bounds on linear2 discovered at level 0.booleanAllows objective sharing between workers.doubleAdd a shaving phase (where the solver tries to prove that the lower or upper bound of a variable are infeasible) to the probing searchdoubleSpecifies the amount of deterministic time spent of each try at shaving a bound in the shaving search.longSpecifies the threshold between two modes in the shaving procedure.intIf solution_pool_size is <= this, we will use DP to keep a "diverse" set of solutions (the one further apart via hamming distance) in the pool.intSize of the top-n different solutions kept by the solver.booleanFor an optimization problem, stop the solver as soon as we have a solution.booleanMainly used when improving the presolver.booleanoptional bool stop_after_root_propagation = 252 [default = false];doubleThe parameter num_conflicts_before_strategy_changes is increased by that much after each strategy change.getSubsolverParams(int index) It is possible to specify additional subsolver configuration.getSubsolverParamsBuilder(int index) It is possible to specify additional subsolver configuration.It is possible to specify additional subsolver configuration.intIt is possible to specify additional subsolver configuration.It is possible to specify additional subsolver configuration.getSubsolverParamsOrBuilder(int index) It is possible to specify additional subsolver configuration.List<? extends SatParametersOrBuilder> It is possible to specify additional subsolver configuration.getSubsolvers(int index) In multi-thread, the solver can be mainly seen as a portfolio of solvers with different parameters.com.google.protobuf.ByteStringgetSubsolversBytes(int index) In multi-thread, the solver can be mainly seen as a portfolio of solvers with different parameters.intIn multi-thread, the solver can be mainly seen as a portfolio of solvers with different parameters.com.google.protobuf.ProtocolStringListIn multi-thread, the solver can be mainly seen as a portfolio of solvers with different parameters.booleanIf we remove clause that we now are "implied" by others.booleanAt a really low cost, during the 1-UIP conflict computation, it is easy to detect if some of the involved reasons are subsumed by the current conflict.doubleDeterministic time limit for symmetry detection.intWhether we try to automatically detect the symmetries in a model and exploit them.intHow much we try to "compress" a table constraint.intAt root level, we might compute the transitive closure of "precedences" relations so that we can exploit that in scheduling problems.booleanoptional bool use_absl_random = 180 [default = false];booleanTurn on extra propagation for the circuit constraint.booleanWhen this is true, the no_overlap_2d constraint is reinforced with an energetic reasoning that uses an area-based energy.booleanBlock a moving restart algorithm if the trail size of the current conflict is greater than the multiplier times the moving average of the trail size at the previous conflicts.booleanIf true, try to backtrack as little as possible on conflict and re-imply the clauses later.booleanThis can be beneficial if there is a lot of no-overlap constraints but a relatively low number of different intervals in the problem.booleanEnable a heuristic to solve cumulative constraints using a modified energy constraint.booleanWhen this is true, the cumulative constraint is reinforced with propagators from the disjunctive constraint to improve the inference on a set of tasks that are disjunctive at the root of the problem.booleanWhen set, it activates a few scheduling parameters to improve the lower bound of scheduling problems.booleanoptional bool use_dynamic_precedence_in_cumulative = 268 [default = false];booleanWhether we try to branch on decision "interval A before interval B" rather than on intervals bounds.booleanWhen this is true, the no_overlap_2d constraint is reinforced with energetic reasoning.booleanWhether we use the ERWA (Exponential Recency Weighted Average) heuristic as described in "Learning Rate Based Branching Heuristic for SAT solvers", J.H.Liang, V.booleanThe solver usually exploit the LP relaxation of a model.booleanUse extended probing (probe bool_or, at_most_one, exactly_one).booleanParameters for an heuristic similar to the one described in the paper: "Feasibility Jump: an LP-free Lagrangian MIP heuristic", Bjørnar Luteberget, Giorgio Sartor, 2023, Mathematical Programming Computation.booleanAdds a feasibility pump subsolver along with lns subsolvers.booleanIf true, detect and create constraint for integer variable that are "after" a set of intervals in the same cumulative constraint.booleanStores and exploits "implied-bounds" in the solver.booleanTurns on neighborhood generator based on local branching LP.booleanWhen set, this activates a propagator for the no_overlap_2d constraint that uses any eventual linear constraints of the model in the form `{start interval 1} - {end interval 2} + c*w <= ub` to detect that two intervals must overlap in one dimension for some values of `w`.booleanTesting parameters used to disable all lns workers.booleanExperimental parameters to disable everything but lns.booleanDisable every other type of subsolver, setting this turns CP-SAT into a pure local-search solver.booleanThis should be better on integer problems.booleanIf true, search will search in ascending max objective value (when minimizing) starting from the lower bound of the objective.booleanThis search differs from the previous search as it will not use assumptions to bound the objective, and it will recreate a full model with the hardcoded objective value.booleanFor an optimization problem, whether we follow some hints in order to find a better first solution.booleanIf true, we automatically detect variables whose constraint are always enforced by the same literal and we mark them as optional.booleanWhen this is true, the cumulative constraint is reinforced with overload checking, i.e., an additional level of reasoning based on energy.booleanExperimental.booleanIf this is true, then the polarity of a variable will be the last value it was assigned to, or its default polarity if it was never assigned since the call to ResetDecisionHeuristic().booleanWhen this is true, then a disjunctive constraint will try to use the precedence relations between time intervals to propagate their bounds further.booleanIf true, search will continuously probe Boolean variables, and integer variable bounds.booleanTurns on relaxation induced neighborhood generator.booleanEnable or disable "inprocessing" which is some SAT presolving done at each restart to the root level.booleanSet on shared subtree workers.booleanEnable stronger and more expensive propagation on no_overlap constraint.booleanWhen we have symmetry, it is possible to "fold" all variables from the same orbit into a single variable, while having the same power of LP relaxation.booleanWhen this is true, the cumulative constraint is reinforced with timetable edge finding, i.e., an additional level of reasoning based on the conjunction of energy and mandatory parts.booleanWhen this is true, the no_overlap_2d constraint is reinforced with propagators from the cumulative constraints.booleanoptional bool use_try_edge_reasoning_in_no_overlap_2d = 299 [default = false];doubleEach time a conflict is found, the activities of some variables are increased by one.intThis search takes all Boolean or integer variables, and maximize or minimize them in order to reduce their domain. -1 is automatic, otherwise value 0 disables it, and 1, 2, or 3 changes something.doubleProbability of using compound move search each restart.intHow long violation_ls should wait before perturbating a solution.booleanStop the search when the gap between the best feasible objective (O) and our best objective bound (B) is smaller than a limit.booleanWhether we generate and add Chvatal-Gomory cuts to the LP at root node.booleanWhether we generate clique cuts from the binary implication graph.booleanFor the lin max constraints, generates the cuts described in "Strong mixed-integer programming formulations for trained neural networks" by Ross Anderson et.booleanIf true, we start by an empty LP, and only add constraints not satisfied by the current LP solution batch by batch.booleanWhether we generate MIR cuts at root node.booleanWhen the LP objective is fractional, do we add the cut that forces the linear objective expression to be greater or equal to this fractional value rounded up?booleanWhether we generate RLT cuts.booleanWhether we generate Zero-Half cuts at root node.booleanWhen this is true, then the variables that appear in any of the reason of the variables in a conflict have their activity bumped.booleanIn order to not get stuck in local optima, when this is non-zero, we try to also work on "older" solutions with a worse objective value so we get a chance to follow a different LS/LNS trajectory.booleanAll at_most_one constraints with a size <= param will be replaced by a quadratic number of binary implications.booleanIf true, then the precedences propagator try to detect for each variable if it has a set of "optional incoming arc" for which at least one of them is present.booleanoptional .operations_research.sat.SatParameters.BinaryMinizationAlgorithm binary_minimization_algorithm = 34 [default = BINARY_MINIMIZATION_FROM_UIP_AND_DECISIONS];booleanIf non-negative, perform a binary search on the objective variable in order to find an [min, max] interval outside of which the solver proved unsat/sat under this amount of conflict.booleanoptional double blocking_restart_multiplier = 66 [default = 1.4];booleanoptional int32 blocking_restart_window_size = 65 [default = 5000];booleanA non-negative level indicating how much we should try to fully encode Integer variables as Boolean.booleanIndicates if the CP-SAT layer should catch Control-C (SIGINT) signals when calling solve.booleanIf true, and if the problem is UNSAT, a DRAT proof of this UNSAT property is checked after the solver has finished.booleanIf true, inferred clauses are checked with an LRAT checker as they are learned, in presolve (reduced to trivial simplifications if cp_model_presolve is false), and in each worker.booleanIf true, and if output_lrat_proof is true and the problem is UNSAT, check that the merged proof file is valid, i.e., that clause sharing between workers is correct.booleanIf chronological backtracking is enabled, this is the minimum number of conflicts before we will consider backjumping.booleanClause activity parameters (same effect as the one on the variables).booleanAll the clauses with a LBD (literal blocks distance) lower or equal to this parameters will always be kept.booleanAll the clause with a LBD lower or equal to this will be kept except if its activity hasn't been bumped in the last 32 cleanup phase.booleanAll the clause with a LBD lower or equal to this will be kept except if its activity hasn't been bumped since the previous cleanup phase.booleanoptional .operations_research.sat.SatParameters.ClauseOrdering clause_cleanup_ordering = 60 [default = CLAUSE_ACTIVITY];booleanTrigger a cleanup when this number of "deletable" clauses is learned.booleanIncrease clause_cleanup_period by this amount after each cleanup.booleanDuring a cleanup, if clause_cleanup_target is 0, we will delete the clause_cleanup_ratio of "deletable" clauses instead of aiming for a fixed target of clauses to keep.booleanDuring a cleanup, we will always keep that number of "deletable" clauses.booleanTemporary flag util the feature is more mature.booleanIf positive, we spend some effort on each core: - At level 1, we use a simple heuristic to try to minimize an UNSAT core. - At level 2, we use propagation to minimize the core but also identify literal in at most one relationship in this core.booleanWhether or not the assumption levels are taken into account during the LBD computation.booleanIf true, when the max-sat algo find a core, we compute the minimal number of literals in the core that needs to be true to have a feasible solution.booleanWhether we presolve the cp_model before solving it.booleanHow much effort do we spend on probing. 0 disables it completely.booleanWhether we also use the sat presolve when cp_model_presolve is true.booleanIf true, and during integer conflict resolution (icr) the 1-UIP is an integer literal for which we do not have an associated Boolean.booleanoptional double cut_active_count_decay = 156 [default = 0.8];booleanTarget number of constraints to remove during cleanup.booleanControl the global cut effort.booleanThese parameters are similar to sat clause management activity parameters.booleanCrash if the LRAT UNSAT proof is invalid.booleanCrash if presolve breaks a feasible hint.booleanCrash if we do not manage to complete the hint into a full solution.booleanIf positive, try to stop just after that many presolve rules have been applied.booleanWe have two different postsolve code.booleanTry even more subsumption options during conflict analysis.booleanoptional string default_restart_algorithms = 70 [default = "LUBY_RESTART,LBD_MOVING_AVERAGE_RESTART,DL_MOVING_AVERAGE_RESTART"];booleanInfer products of Boolean or of Boolean time IntegerVariable from the linear constrainst in the problem.booleanIf true, we detect variable that are unique to a table constraint and only there to encode a cost on each tuple.booleanIf true, it disable all constraint expansion.booleanIf true, registers more lns subsolvers with different parameters.booleanIf >=0, each time we have a conflict, we try to subsume the last n learned clause with it.booleanLinear constraint with a complex right hand side (more than a single interval) need to be expanded, there is a couple of way to do that.booleanEncore cumulative with fixed demands and capacity as a reservoir constraint.booleanWhether we enumerate all solutions of a problem without objective.booleanIf true, expand all_different constraints that are not permutations.booleanIf true, expand the reservoir constraints by creating booleans for all possible precedences between event and encoding the constraint.booleanMainly useful for testing.booleanIf true and the Lp relaxation of the problem has a solution, try to exploit it.booleanoptional bool exploit_all_precedences = 220 [default = false];booleanWhen branching on a variable, follow the last best solution value.booleanIf true and the Lp relaxation of the problem has an integer optimal solution, try to exploit it.booleanWhen branching an a variable that directly affect the objective, branch on the value that lead to the best objective first.booleanWhen branching on a variable, follow the last best relaxation solution value.booleanIt is possible that "intermediate" clauses during conflict resolution subsumes some of the clauses that propagated.booleanHow much dtime for each LS batch.booleanOn each restart, we randomly choose if we use decay (with this parameter) or no decay.booleanWhen stagnating, feasibility jump will either restart from a default solution (with some possible randomization), or randomly pertubate the current solution.booleanHow much do we linearize the problem in the local search code.booleanMaximum size of no_overlap or no_overlap_2d constraint for a quadratic expansion.booleanThis is a factor that directly influence the work before each restart.booleanMax distance between the default value and the pertubated value relative to the range of the domain of the variable.booleanProbability for a variable to have a non default value upon restarts or perturbations.booleanIf true, the final response addition_solutions field will be filled with all solutions from our solutions pool.booleanIf true, add information about the derived variable domains to the CpSolverResponse.booleanInternal parameter.booleanTry to find large "rectangle" in the linear constraint matrix with identical lines.booleanBy propagating (or just using binary clauses), one can detect that all literal of a clause are actually in at most one relationship.booleanWhether we try to find more independent cores for a given set of assumptions in the core based max-SAT algorithms.booleanIf true, variables appearing in the solution hints will be fixed to their hinted value.booleanoptional .operations_research.sat.SatParameters.FPRoundingMethod fp_rounding = 165 [default = PROPAGATION_ASSISTED];booleanoptional double glucose_decay_increment = 23 [default = 0.01];booleanoptional int32 glucose_decay_increment_period = 24 [default = 5000];booleanThe activity starts at 0.8 and increment by 0.01 every 5000 conflicts until 0.95.booleanConflict limit used in the phase that exploit the solution hint.booleanIf true, we don't keep names in our internal copy of the user given model.booleanRun a max-clique code amongst all the x !booleanoptional .operations_research.sat.SatParameters.Polarity initial_polarity = 2 [default = POLARITY_FALSE];booleanThe initial value of the variables activity.booleanProportion of deterministic time we should spend on inprocessing.booleanParameters for an heuristic similar to the one described in "An effective learnt clause minimization approach for CDCL Sat Solvers", https://www.ijcai.org/proceedings/2017/0098.pdf This is the amount of dtime we should spend on this technique during each inprocessing phase.booleanoptional bool inprocessing_minimization_use_all_orderings = 298 [default = false];booleanoptional bool inprocessing_minimization_use_conflict_analysis = 297 [default = true];booleanThe amount of dtime we should spend on probing for each inprocessing round.booleanWhether we use the algorithm described in "Clausal Congruence closure", Armin Biere, Katalin Fazekas, Mathias Fleury, Nils Froleyks, 2024.booleanWhether we use the SAT sweeping algorithm described in "Clausal Equivalence Sweeping", Armin Biere, Katalin Fazekas, Mathias Fleury, Nils Froleyks, 2025.booleanIf true, the solver will add a default integer branching strategy to the already defined search strategy.booleanoptional int32 interleave_batch_size = 134 [default = 0];booleanExperimental.booleanIf true, we disable the presolve reductions that remove feasible solutions from the search space.booleanExperimental.booleanOnly use lb-relax if we have at least that many workers.booleanA non-negative level indicating the type of constraints we consider in the LP relaxation.booleanLinear constraints that are not pseudo-Boolean and that are longer than this size will be split into sqrt(size) intermediate sums in order to have faster propation in the CP engine.booleanoptional double lns_initial_deterministic_limit = 308 [default = 0.1];booleanInitial parameters for neighborhood generation.booleanIf we try to load at most ones and exactly ones constraints when running the pure SAT presolve.booleanAdd a prefix to all logs.booleanWhether the solver should log the search progress.booleanWhether the solver should display per sub-solver search statistics.booleanLog to response proto.booleanLog to stdout.booleanoptional double lp_dual_tolerance = 267 [default = 1e-07];booleanThe internal LP tolerances used by CP-SAT.booleanCut generator for all diffs can add too many cuts for large all_diff constraints.booleanMax domain size for all_different constraints to be expanded.booleanIf chronological backtracking is enabled, this is the maximum number of levels we will backjump over, otherwise we will backtrack.booleanoptional double max_clause_activity_value = 18 [default = 1e+20];booleanIf a constraint/cut in LP is not active for that many consecutive OPTIMAL solves, remove it from the LP.booleanMax number of time we perform cut generation and resolve the LP at level 0.booleanMaximum time allowed in deterministic time to solve a problem.booleanMax domain size for expanding linear2 constraints (ax + by ==/!booleanWhen loading a*x + b*y ==/!booleanThe maximum time allowed to check the DRAT proof (this can take more time than the solve itself).booleanDetects when the space where items of a no_overlap_2d constraint can placed is disjoint (ie., fixed boxes split the domain).booleanIn the integer rounding procedure used for MIR and Gomory cut, the maximum "scaling" we use (must be positive).booleanIf the number of expressions in the lin_max is less that the max size parameter, model expansion replaces target = max(xi) by linear constraint with the introduction of new booleans bi such that bi => target == xi.booleanMaximum memory allowed for the whole thread containing the solver.booleanMaximum number of conflicts allowed to solve a problem.booleanThe limit on the number of cuts in our cut pool.booleanStops after that number of batches has been scheduled.booleanMax number of intervals for the timetable_edge_finding algorithm to propagate.booleanIf the number of pairs to look is below this threshold, do an extra step of propagation in the no_overlap_2d constraint by looking at all pairs of intervals.booleanIn case of large reduction in a presolve iteration, we perform multiple presolve iterations.booleanoptional .operations_research.sat.SatParameters.MaxSatAssumptionOrder max_sat_assumption_order = 51 [default = DEFAULT_ASSUMPTION_ORDER];booleanIf true, adds the assumption in the reverse order of the one defined by max_sat_assumption_order.booleanoptional .operations_research.sat.SatParameters.MaxSatStratificationAlgorithm max_sat_stratification = 53 [default = STRATIFICATION_DESCENT];booleanCreate one literal for each disjunction of two pairs of tasks.booleanMaximum time allowed in seconds to solve a problem.booleanoptional double max_variable_activity_value = 16 [default = 1e+100];booleanoptional double merge_at_most_one_work_limit = 146 [default = 100000000];booleanDuring presolve, we use a maximum clique heuristic to merge together no-overlap constraints or at most one constraints.booleanoptional .operations_research.sat.SatParameters.ConflictMinimizationAlgorithm minimization_algorithm = 4 [default = RECURSIVE];booleanA different algorithm during PB resolution.booleanMinimize and detect subsumption of shared clauses immediately after they are imported.booleanWhile adding constraints, skip the constraints which have orthogonality less than 'min_orthogonality_for_lp_constraints' with already added constraints during current call.booleanIf true, some continuous variable might be automatically scaled.booleanAs explained in mip_precision and mip_max_activity_exponent, we cannot always reach the wanted precision during scaling.booleanEven if we make big error when scaling the objective, we can always derive a correct lower bound on the original objective by using the exact lower bound on the scaled integer version of the objective.booleanAny value in the input mip with a magnitude lower than this will be set to zero.booleanTo avoid integer overflow, we always force the maximum possible constraint activity (and objective value) according to the initial variable domain to be smaller than 2 to this given power.booleanWe need to bound the maximum magnitude of the variables for CP-SAT, and that is the bound we use.booleanAny finite values in the input MIP must be below this threshold, otherwise the model will be reported invalid.booleanWhen solving a MIP, we do some basic floating point presolving before scaling the problem to integer to be handled by CP-SAT.booleanIf this is false, then mip_var_scaling is only applied to variables with "small" domain.booleanBy default, any variable/constraint bound with a finite value and a magnitude greater than the mip_max_valid_magnitude will result with a invalid model.booleanAll continuous variable of the problem will be multiplied by this factor.booleanWhen scaling constraint with double coefficients to integer coefficients, we will multiply by a power of 2 and round the coefficients.booleanhasName()In some context, like in a portfolio of search, it makes sense to name a given parameters set for logging purpose.booleanAdd that many lazy constraints (or cuts) at once in the LP.booleanThe new linear propagation code treat all constraints at once and use an adaptation of Bellman-Ford-Tarjan to propagate constraint in a smarter order and potentially detect propagation cycle earlier.booleanIf less than this number of boxes are present in a no-overlap 2d, we create 4 Booleans per pair of boxes: - Box 2 is after Box 1 on x. - Box 1 is after Box 2 on x. - Box 2 is after Box 1 on y. - Box 1 is after Box 2 on y.booleanAfter each restart, if the number of conflict since the last strategy change is greater that this, then we increment a "strategy_counter" that can be use to change the search strategy used by the following restarts.booleanWe distinguish subsolvers that consume a full thread, and the ones that are always interleaved.booleanoptional int32 num_search_workers = 100 [default = 0];booleanThis will create incomplete subsolvers (that are not LNS subsolvers) that use the feasibility jump code to find improving solution, treating the objective improvement as a hard constraint.booleanSpecify the number of parallel workers (i.e. threads) to use during search.booleanFor the cut that can be generated at any level, this control if we only try to generate them at the root node.booleanIf one try to solve a MIP model with CP-SAT, because we assume all variable to be integer after scaling, we will not necessarily have the correct optimal.booleanThe default optimization method is a simple "linear scan", each time trying to find a better solution than the previous one.booleanDo a more conventional tree search (by opposition to SAT based one) where we keep all the explored node in a tree.booleanThis has no effect if optimize_with_core is false.booleanIf true, a DRAT proof that all the clauses inferred by the solver are valid is output to a file.booleanIf true, an LRAT proof that all the clauses inferred by the solver are valid is output to several files (one for presolve -- reduced to trivial simplifications if cp_model_presolve is false, one per worker, and one for the merged proof).booleanSame as for the clauses, but for the learned pseudo-Boolean constraints.booleanoptional double pb_cleanup_ratio = 47 [default = 0.5];booleanoptional bool permute_presolve_constraint_order = 179 [default = false];booleanThis is mainly here to test the solver variability.booleanIf true and we have first solution LS workers, tries in some phase to follow a LS solutions that violates has litle constraints as possible.booleanIf non-zero, then we change the polarity heuristic after that many number of conflicts in an arithmetically increasing fashion.booleanWhether we try to do a few degenerate iteration at the end of an LP solve to minimize the fractionality of the integer variable in the basis.booleanoptional .operations_research.sat.SatParameters.VariableOrder preferred_variable_order = 1 [default = IN_ORDER];booleanWhether we use an heuristic to detect some basic case of blocked clause in the SAT presolve.booleanApply Bounded Variable Addition (BVA) if the number of clauses is reduced by stricly more than this threshold.booleanDuring presolve, we apply BVE only if this weight times the number of clauses plus the number of clause literals is not increased.booleanDuring presolve, only try to perform the bounded variable elimination (BVE) of a variable x if the number of occurrences of x times the number of occurrences of not(x) is not greater than this parameter.booleanIf true, we will extract from linear constraints, enforcement literals of the form "integer variable at bound => simplified constraint".booleanA few presolve operations involve detecting constraints included in other constraint.booleanoptional double presolve_probing_deterministic_time_limit = 57 [default = 30];booleanHow much substitution (also called free variable aggregation in MIP litterature) should we perform at presolve.booleanWhether or not we use Bounded Variable Addition (BVA) in the presolve.booleanThe maximum "deterministic" time limit to spend in probing.booleanHow many combinations of pairs or triplets of variables we want to scan.booleanSome search decisions might cause a really large number of propagations to happen when integer variables with large domains are only reduced by 1 at each step.booleanThe solver ignores the pseudo costs of variables with number of recordings less than this threshold.booleanExperimental code: specify if the objective pushes all tasks toward the start of the schedule.booleanA number between 0 and 1 that indicates the proportion of branching variables that are selected randomly instead of choosing the first variable from the given variable_ordering strategy.booleanRandomize fixed search.booleanThe proportion of polarity chosen at random.booleanAt the beginning of each solve, the random number generator used in some part of the solver is reinitialized to this seed.booleanoptional double relative_gap_limit = 160 [default = 0];booleanIf cp_model_presolve is true and there is a large proportion of fixed variable after the first model copy, remap all the model to a dense set of variable before the full presolve even starts.booleanIf true, the solver tries to repair the solution given in the hint.booleanIn the moving average restart algorithms, a restart is triggered if the window average times this ratio is greater that the global average.booleanoptional double restart_lbd_average_ratio = 71 [default = 1];booleanRestart period for the FIXED_RESTART strategy.booleanSize of the window for the moving average restarts.booleanEven at the root node, we do not want to spend too much time on the LP if it is "difficult".booleanThe amount of "effort" to spend in dynamic programming for computing routing cuts.booleanIf the length of an infeasible path is less than this value, a cut will be added to exclude it.booleanIf the size of a subset of nodes of a RoutesConstraint is less than this value, use linear constraints of size 1 and 2 (such as capacity and time window constraints) enforced by the arc literals to compute cuts for this subset (unless the subset size is less than routing_cut_subset_size_for_tight_binary_relation_bound, in which case the corresponding algorithm is used instead).booleanSimilar to above, but with an even stronger algorithm in O(n!).booleanSimilar to routing_cut_subset_size_for_exact_binary_relation_bound but use a bound based on shortest path distances (which respect triangular inequality).booleanSimilar to above, but with a different algorithm producing better cuts, at the price of a higher O(2^n) complexity, where n is the subset size.booleanExperimental.booleanoptional .operations_research.sat.SatParameters.SearchBranching search_branching = 82 [default = AUTOMATIC_SEARCH];booleanSearch randomization will collect the top 'search_random_variable_pool_size' valued variables, and pick one randomly.booleanAllows sharing of new learned binary clause between workers.booleanHow much deeper compared to the ideal max depth of the tree is considered "balanced" enough to still accept a split.booleanIn order to limit total shared memory and communication overhead, limit the total number of nodes that may be generated in the shared tree.booleanEnables shared tree search.booleanHow many open leaf nodes should the shared tree maintain per worker.booleanHow much dtime a worker will wait between proposing splits.booleanoptional .operations_research.sat.SatParameters.SharedTreeSplitStrategy shared_tree_split_strategy = 239 [default = SPLIT_STRATEGY_AUTO];booleanIf true, shared tree workers share their target phase when returning an assigned subtree for the next worker to use.booleanIf true, workers share more of the information from their local trail.booleanMinimum restarts before a worker will replace a subtree that looks "bad" based on the average LBD of learned clauses.booleanAllows sharing of short glue clauses between workers.booleanThe amount of dtime between each export of shared glue clauses.booleanAllows sharing of the bounds of modified variables at level 0.booleanAllows sharing of the bounds on linear2 discovered at level 0.booleanAllows objective sharing between workers.booleanAdd a shaving phase (where the solver tries to prove that the lower or upper bound of a variable are infeasible) to the probing searchbooleanSpecifies the amount of deterministic time spent of each try at shaving a bound in the shaving search.booleanSpecifies the threshold between two modes in the shaving procedure.booleanIf solution_pool_size is <= this, we will use DP to keep a "diverse" set of solutions (the one further apart via hamming distance) in the pool.booleanSize of the top-n different solutions kept by the solver.booleanFor an optimization problem, stop the solver as soon as we have a solution.booleanMainly used when improving the presolver.booleanoptional bool stop_after_root_propagation = 252 [default = false];booleanThe parameter num_conflicts_before_strategy_changes is increased by that much after each strategy change.booleanIf we remove clause that we now are "implied" by others.booleanAt a really low cost, during the 1-UIP conflict computation, it is easy to detect if some of the involved reasons are subsumed by the current conflict.booleanDeterministic time limit for symmetry detection.booleanWhether we try to automatically detect the symmetries in a model and exploit them.booleanHow much we try to "compress" a table constraint.booleanAt root level, we might compute the transitive closure of "precedences" relations so that we can exploit that in scheduling problems.booleanoptional bool use_absl_random = 180 [default = false];booleanTurn on extra propagation for the circuit constraint.booleanWhen this is true, the no_overlap_2d constraint is reinforced with an energetic reasoning that uses an area-based energy.booleanBlock a moving restart algorithm if the trail size of the current conflict is greater than the multiplier times the moving average of the trail size at the previous conflicts.booleanIf true, try to backtrack as little as possible on conflict and re-imply the clauses later.booleanThis can be beneficial if there is a lot of no-overlap constraints but a relatively low number of different intervals in the problem.booleanEnable a heuristic to solve cumulative constraints using a modified energy constraint.booleanWhen this is true, the cumulative constraint is reinforced with propagators from the disjunctive constraint to improve the inference on a set of tasks that are disjunctive at the root of the problem.booleanWhen set, it activates a few scheduling parameters to improve the lower bound of scheduling problems.booleanoptional bool use_dynamic_precedence_in_cumulative = 268 [default = false];booleanWhether we try to branch on decision "interval A before interval B" rather than on intervals bounds.booleanWhen this is true, the no_overlap_2d constraint is reinforced with energetic reasoning.booleanWhether we use the ERWA (Exponential Recency Weighted Average) heuristic as described in "Learning Rate Based Branching Heuristic for SAT solvers", J.H.Liang, V.booleanThe solver usually exploit the LP relaxation of a model.booleanUse extended probing (probe bool_or, at_most_one, exactly_one).booleanParameters for an heuristic similar to the one described in the paper: "Feasibility Jump: an LP-free Lagrangian MIP heuristic", Bjørnar Luteberget, Giorgio Sartor, 2023, Mathematical Programming Computation.booleanAdds a feasibility pump subsolver along with lns subsolvers.booleanIf true, detect and create constraint for integer variable that are "after" a set of intervals in the same cumulative constraint.booleanStores and exploits "implied-bounds" in the solver.booleanTurns on neighborhood generator based on local branching LP.booleanWhen set, this activates a propagator for the no_overlap_2d constraint that uses any eventual linear constraints of the model in the form `{start interval 1} - {end interval 2} + c*w <= ub` to detect that two intervals must overlap in one dimension for some values of `w`.booleanTesting parameters used to disable all lns workers.booleanExperimental parameters to disable everything but lns.booleanDisable every other type of subsolver, setting this turns CP-SAT into a pure local-search solver.booleanThis should be better on integer problems.booleanIf true, search will search in ascending max objective value (when minimizing) starting from the lower bound of the objective.booleanThis search differs from the previous search as it will not use assumptions to bound the objective, and it will recreate a full model with the hardcoded objective value.booleanFor an optimization problem, whether we follow some hints in order to find a better first solution.booleanIf true, we automatically detect variables whose constraint are always enforced by the same literal and we mark them as optional.booleanWhen this is true, the cumulative constraint is reinforced with overload checking, i.e., an additional level of reasoning based on energy.booleanExperimental.booleanIf this is true, then the polarity of a variable will be the last value it was assigned to, or its default polarity if it was never assigned since the call to ResetDecisionHeuristic().booleanWhen this is true, then a disjunctive constraint will try to use the precedence relations between time intervals to propagate their bounds further.booleanIf true, search will continuously probe Boolean variables, and integer variable bounds.booleanTurns on relaxation induced neighborhood generator.booleanEnable or disable "inprocessing" which is some SAT presolving done at each restart to the root level.booleanSet on shared subtree workers.booleanEnable stronger and more expensive propagation on no_overlap constraint.booleanWhen we have symmetry, it is possible to "fold" all variables from the same orbit into a single variable, while having the same power of LP relaxation.booleanWhen this is true, the cumulative constraint is reinforced with timetable edge finding, i.e., an additional level of reasoning based on the conjunction of energy and mandatory parts.booleanWhen this is true, the no_overlap_2d constraint is reinforced with propagators from the cumulative constraints.booleanoptional bool use_try_edge_reasoning_in_no_overlap_2d = 299 [default = false];booleanEach time a conflict is found, the activities of some variables are increased by one.booleanThis search takes all Boolean or integer variables, and maximize or minimize them in order to reduce their domain. -1 is automatic, otherwise value 0 disables it, and 1, 2, or 3 changes something.booleanProbability of using compound move search each restart.booleanHow long violation_ls should wait before perturbating a solution.protected com.google.protobuf.GeneratedMessage.FieldAccessorTablefinal booleanmergeFrom(SatParameters other) mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) mergeFrom(com.google.protobuf.Message other) removeSubsolverParams(int index) It is possible to specify additional subsolver configuration.setAbsoluteGapLimit(double value) Stop the search when the gap between the best feasible objective (O) and our best objective bound (B) is smaller than a limit.setAddCgCuts(boolean value) Whether we generate and add Chvatal-Gomory cuts to the LP at root node.setAddCliqueCuts(boolean value) Whether we generate clique cuts from the binary implication graph.setAddLinMaxCuts(boolean value) For the lin max constraints, generates the cuts described in "Strong mixed-integer programming formulations for trained neural networks" by Ross Anderson et.setAddLpConstraintsLazily(boolean value) If true, we start by an empty LP, and only add constraints not satisfied by the current LP solution batch by batch.setAddMirCuts(boolean value) Whether we generate MIR cuts at root node.setAddObjectiveCut(boolean value) When the LP objective is fractional, do we add the cut that forces the linear objective expression to be greater or equal to this fractional value rounded up?setAddRltCuts(boolean value) Whether we generate RLT cuts.setAddZeroHalfCuts(boolean value) Whether we generate Zero-Half cuts at root node.setAlsoBumpVariablesInConflictReasons(boolean value) When this is true, then the variables that appear in any of the reason of the variables in a conflict have their activity bumped.setAlternativePoolSize(int value) In order to not get stuck in local optima, when this is non-zero, we try to also work on "older" solutions with a worse objective value so we get a chance to follow a different LS/LNS trajectory.setAtMostOneMaxExpansionSize(int value) All at_most_one constraints with a size <= param will be replaced by a quadratic number of binary implications.setAutoDetectGreaterThanAtLeastOneOf(boolean value) If true, then the precedences propagator try to detect for each variable if it has a set of "optional incoming arc" for which at least one of them is present.optional .operations_research.sat.SatParameters.BinaryMinizationAlgorithm binary_minimization_algorithm = 34 [default = BINARY_MINIMIZATION_FROM_UIP_AND_DECISIONS];setBinarySearchNumConflicts(int value) If non-negative, perform a binary search on the objective variable in order to find an [min, max] interval outside of which the solver proved unsat/sat under this amount of conflict.setBlockingRestartMultiplier(double value) optional double blocking_restart_multiplier = 66 [default = 1.4];setBlockingRestartWindowSize(int value) optional int32 blocking_restart_window_size = 65 [default = 5000];setBooleanEncodingLevel(int value) A non-negative level indicating how much we should try to fully encode Integer variables as Boolean.setCatchSigintSignal(boolean value) Indicates if the CP-SAT layer should catch Control-C (SIGINT) signals when calling solve.setCheckDratProof(boolean value) If true, and if the problem is UNSAT, a DRAT proof of this UNSAT property is checked after the solver has finished.setCheckLratProof(boolean value) If true, inferred clauses are checked with an LRAT checker as they are learned, in presolve (reduced to trivial simplifications if cp_model_presolve is false), and in each worker.setCheckMergedLratProof(boolean value) If true, and if output_lrat_proof is true and the problem is UNSAT, check that the merged proof file is valid, i.e., that clause sharing between workers is correct.setChronologicalBacktrackMinConflicts(int value) If chronological backtracking is enabled, this is the minimum number of conflicts before we will consider backjumping.setClauseActivityDecay(double value) Clause activity parameters (same effect as the one on the variables).setClauseCleanupLbdBound(int value) All the clauses with a LBD (literal blocks distance) lower or equal to this parameters will always be kept.setClauseCleanupLbdTier1(int value) All the clause with a LBD lower or equal to this will be kept except if its activity hasn't been bumped in the last 32 cleanup phase.setClauseCleanupLbdTier2(int value) All the clause with a LBD lower or equal to this will be kept except if its activity hasn't been bumped since the previous cleanup phase.optional .operations_research.sat.SatParameters.ClauseOrdering clause_cleanup_ordering = 60 [default = CLAUSE_ACTIVITY];setClauseCleanupPeriod(int value) Trigger a cleanup when this number of "deletable" clauses is learned.setClauseCleanupPeriodIncrement(int value) Increase clause_cleanup_period by this amount after each cleanup.setClauseCleanupRatio(double value) During a cleanup, if clause_cleanup_target is 0, we will delete the clause_cleanup_ratio of "deletable" clauses instead of aiming for a fixed target of clauses to keep.setClauseCleanupTarget(int value) During a cleanup, we will always keep that number of "deletable" clauses.setConvertIntervals(boolean value) Temporary flag util the feature is more mature.setCoreMinimizationLevel(int value) If positive, we spend some effort on each core: - At level 1, we use a simple heuristic to try to minimize an UNSAT core. - At level 2, we use propagation to minimize the core but also identify literal in at most one relationship in this core.setCountAssumptionLevelsInLbd(boolean value) Whether or not the assumption levels are taken into account during the LBD computation.setCoverOptimization(boolean value) If true, when the max-sat algo find a core, we compute the minimal number of literals in the core that needs to be true to have a feasible solution.setCpModelPresolve(boolean value) Whether we presolve the cp_model before solving it.setCpModelProbingLevel(int value) How much effort do we spend on probing. 0 disables it completely.setCpModelUseSatPresolve(boolean value) Whether we also use the sat presolve when cp_model_presolve is true.setCreate1UipBooleanDuringIcr(boolean value) If true, and during integer conflict resolution (icr) the 1-UIP is an integer literal for which we do not have an associated Boolean.setCutActiveCountDecay(double value) optional double cut_active_count_decay = 156 [default = 0.8];setCutCleanupTarget(int value) Target number of constraints to remove during cleanup.setCutLevel(int value) Control the global cut effort.setCutMaxActiveCountValue(double value) These parameters are similar to sat clause management activity parameters.setDebugCrashIfLratCheckFails(boolean value) Crash if the LRAT UNSAT proof is invalid.setDebugCrashIfPresolveBreaksHint(boolean value) Crash if presolve breaks a feasible hint.setDebugCrashOnBadHint(boolean value) Crash if we do not manage to complete the hint into a full solution.setDebugMaxNumPresolveOperations(int value) If positive, try to stop just after that many presolve rules have been applied.setDebugPostsolveWithFullSolver(boolean value) We have two different postsolve code.setDecisionSubsumptionDuringConflictAnalysis(boolean value) Try even more subsumption options during conflict analysis.optional string default_restart_algorithms = 70 [default = "LUBY_RESTART,LBD_MOVING_AVERAGE_RESTART,DL_MOVING_AVERAGE_RESTART"];setDefaultRestartAlgorithmsBytes(com.google.protobuf.ByteString value) optional string default_restart_algorithms = 70 [default = "LUBY_RESTART,LBD_MOVING_AVERAGE_RESTART,DL_MOVING_AVERAGE_RESTART"];setDetectLinearizedProduct(boolean value) Infer products of Boolean or of Boolean time IntegerVariable from the linear constrainst in the problem.setDetectTableWithCost(boolean value) If true, we detect variable that are unique to a table constraint and only there to encode a cost on each tuple.setDisableConstraintExpansion(boolean value) If true, it disable all constraint expansion.setDiversifyLnsParams(boolean value) If true, registers more lns subsolvers with different parameters.setEagerlySubsumeLastNConflicts(int value) If >=0, each time we have a conflict, we try to subsume the last n learned clause with it.setEncodeComplexLinearConstraintWithInteger(boolean value) Linear constraint with a complex right hand side (more than a single interval) need to be expanded, there is a couple of way to do that.setEncodeCumulativeAsReservoir(boolean value) Encore cumulative with fixed demands and capacity as a reservoir constraint.setEnumerateAllSolutions(boolean value) Whether we enumerate all solutions of a problem without objective.setExpandAlldiffConstraints(boolean value) If true, expand all_different constraints that are not permutations.setExpandReservoirConstraints(boolean value) If true, expand the reservoir constraints by creating booleans for all possible precedences between event and encoding the constraint.setExpandReservoirUsingCircuit(boolean value) Mainly useful for testing.setExploitAllLpSolution(boolean value) If true and the Lp relaxation of the problem has a solution, try to exploit it.setExploitAllPrecedences(boolean value) optional bool exploit_all_precedences = 220 [default = false];setExploitBestSolution(boolean value) When branching on a variable, follow the last best solution value.setExploitIntegerLpSolution(boolean value) If true and the Lp relaxation of the problem has an integer optimal solution, try to exploit it.setExploitObjective(boolean value) When branching an a variable that directly affect the objective, branch on the value that lead to the best objective first.setExploitRelaxationSolution(boolean value) When branching on a variable, follow the last best relaxation solution value.setExtraSubsolvers(int index, String value) A convenient way to add more workers types.setExtraSubsumptionDuringConflictAnalysis(boolean value) It is possible that "intermediate" clauses during conflict resolution subsumes some of the clauses that propagated.setFeasibilityJumpBatchDtime(double value) How much dtime for each LS batch.setFeasibilityJumpDecay(double value) On each restart, we randomly choose if we use decay (with this parameter) or no decay.setFeasibilityJumpEnableRestarts(boolean value) When stagnating, feasibility jump will either restart from a default solution (with some possible randomization), or randomly pertubate the current solution.setFeasibilityJumpLinearizationLevel(int value) How much do we linearize the problem in the local search code.setFeasibilityJumpMaxExpandedConstraintSize(int value) Maximum size of no_overlap or no_overlap_2d constraint for a quadratic expansion.setFeasibilityJumpRestartFactor(int value) This is a factor that directly influence the work before each restart.setFeasibilityJumpVarPerburbationRangeRatio(double value) Max distance between the default value and the pertubated value relative to the range of the domain of the variable.setFeasibilityJumpVarRandomizationProbability(double value) Probability for a variable to have a non default value upon restarts or perturbations.setFillAdditionalSolutionsInResponse(boolean value) If true, the final response addition_solutions field will be filled with all solutions from our solutions pool.setFillTightenedDomainsInResponse(boolean value) If true, add information about the derived variable domains to the CpSolverResponse.setFilterSatPostsolveClauses(boolean value) Internal parameter.setFilterSubsolvers(int index, String value) repeated string filter_subsolvers = 293;setFindBigLinearOverlap(boolean value) Try to find large "rectangle" in the linear constraint matrix with identical lines.setFindClausesThatAreExactlyOne(boolean value) By propagating (or just using binary clauses), one can detect that all literal of a clause are actually in at most one relationship.setFindMultipleCores(boolean value) Whether we try to find more independent cores for a given set of assumptions in the core based max-SAT algorithms.setFixVariablesToTheirHintedValue(boolean value) If true, variables appearing in the solution hints will be fixed to their hinted value.optional .operations_research.sat.SatParameters.FPRoundingMethod fp_rounding = 165 [default = PROPAGATION_ASSISTED];setGlucoseDecayIncrement(double value) optional double glucose_decay_increment = 23 [default = 0.01];setGlucoseDecayIncrementPeriod(int value) optional int32 glucose_decay_increment_period = 24 [default = 5000];setGlucoseMaxDecay(double value) The activity starts at 0.8 and increment by 0.01 every 5000 conflicts until 0.95.setHintConflictLimit(int value) Conflict limit used in the phase that exploit the solution hint.setIgnoreNames(boolean value) If true, we don't keep names in our internal copy of the user given model.setIgnoreSubsolvers(int index, String value) Rather than fully specifying subsolvers, it is often convenient to just remove the ones that are not useful on a given problem or only keep specific ones for testing.setInferAllDiffs(boolean value) Run a max-clique code amongst all the x !optional .operations_research.sat.SatParameters.Polarity initial_polarity = 2 [default = POLARITY_FALSE];setInitialVariablesActivity(double value) The initial value of the variables activity.setInprocessingDtimeRatio(double value) Proportion of deterministic time we should spend on inprocessing.setInprocessingMinimizationDtime(double value) Parameters for an heuristic similar to the one described in "An effective learnt clause minimization approach for CDCL Sat Solvers", https://www.ijcai.org/proceedings/2017/0098.pdf This is the amount of dtime we should spend on this technique during each inprocessing phase.setInprocessingMinimizationUseAllOrderings(boolean value) optional bool inprocessing_minimization_use_all_orderings = 298 [default = false];setInprocessingMinimizationUseConflictAnalysis(boolean value) optional bool inprocessing_minimization_use_conflict_analysis = 297 [default = true];setInprocessingProbingDtime(double value) The amount of dtime we should spend on probing for each inprocessing round.setInprocessingUseCongruenceClosure(boolean value) Whether we use the algorithm described in "Clausal Congruence closure", Armin Biere, Katalin Fazekas, Mathias Fleury, Nils Froleyks, 2024.setInprocessingUseSatSweeping(boolean value) Whether we use the SAT sweeping algorithm described in "Clausal Equivalence Sweeping", Armin Biere, Katalin Fazekas, Mathias Fleury, Nils Froleyks, 2025.setInstantiateAllVariables(boolean value) If true, the solver will add a default integer branching strategy to the already defined search strategy.setInterleaveBatchSize(int value) optional int32 interleave_batch_size = 134 [default = 0];setInterleaveSearch(boolean value) Experimental.setKeepAllFeasibleSolutionsInPresolve(boolean value) If true, we disable the presolve reductions that remove feasible solutions from the search space.setKeepSymmetryInPresolve(boolean value) Experimental.setLbRelaxNumWorkersThreshold(int value) Only use lb-relax if we have at least that many workers.setLinearizationLevel(int value) A non-negative level indicating the type of constraints we consider in the LP relaxation.setLinearSplitSize(int value) Linear constraints that are not pseudo-Boolean and that are longer than this size will be split into sqrt(size) intermediate sums in order to have faster propation in the CP engine.setLnsInitialDeterministicLimit(double value) optional double lns_initial_deterministic_limit = 308 [default = 0.1];setLnsInitialDifficulty(double value) Initial parameters for neighborhood generation.setLoadAtMostOnesInSatPresolve(boolean value) If we try to load at most ones and exactly ones constraints when running the pure SAT presolve.setLogPrefix(String value) Add a prefix to all logs.setLogPrefixBytes(com.google.protobuf.ByteString value) Add a prefix to all logs.setLogSearchProgress(boolean value) Whether the solver should log the search progress.setLogSubsolverStatistics(boolean value) Whether the solver should display per sub-solver search statistics.setLogToResponse(boolean value) Log to response proto.setLogToStdout(boolean value) Log to stdout.setLpDualTolerance(double value) optional double lp_dual_tolerance = 267 [default = 1e-07];setLpPrimalTolerance(double value) The internal LP tolerances used by CP-SAT.setMaxAllDiffCutSize(int value) Cut generator for all diffs can add too many cuts for large all_diff constraints.setMaxAlldiffDomainSize(int value) Max domain size for all_different constraints to be expanded.setMaxBackjumpLevels(int value) If chronological backtracking is enabled, this is the maximum number of levels we will backjump over, otherwise we will backtrack.setMaxClauseActivityValue(double value) optional double max_clause_activity_value = 18 [default = 1e+20];setMaxConsecutiveInactiveCount(int value) If a constraint/cut in LP is not active for that many consecutive OPTIMAL solves, remove it from the LP.setMaxCutRoundsAtLevelZero(int value) Max number of time we perform cut generation and resolve the LP at level 0.setMaxDeterministicTime(double value) Maximum time allowed in deterministic time to solve a problem.setMaxDomainSizeForLinear2Expansion(int value) Max domain size for expanding linear2 constraints (ax + by ==/!setMaxDomainSizeWhenEncodingEqNeqConstraints(int value) When loading a*x + b*y ==/!setMaxDratTimeInSeconds(double value) The maximum time allowed to check the DRAT proof (this can take more time than the solve itself).Detects when the space where items of a no_overlap_2d constraint can placed is disjoint (ie., fixed boxes split the domain).setMaxIntegerRoundingScaling(int value) In the integer rounding procedure used for MIR and Gomory cut, the maximum "scaling" we use (must be positive).setMaxLinMaxSizeForExpansion(int value) If the number of expressions in the lin_max is less that the max size parameter, model expansion replaces target = max(xi) by linear constraint with the introduction of new booleans bi such that bi => target == xi.setMaxMemoryInMb(long value) Maximum memory allowed for the whole thread containing the solver.setMaxNumberOfConflicts(long value) Maximum number of conflicts allowed to solve a problem.setMaxNumCuts(int value) The limit on the number of cuts in our cut pool.setMaxNumDeterministicBatches(int value) Stops after that number of batches has been scheduled.setMaxNumIntervalsForTimetableEdgeFinding(int value) Max number of intervals for the timetable_edge_finding algorithm to propagate.setMaxPairsPairwiseReasoningInNoOverlap2D(int value) If the number of pairs to look is below this threshold, do an extra step of propagation in the no_overlap_2d constraint by looking at all pairs of intervals.setMaxPresolveIterations(int value) In case of large reduction in a presolve iteration, we perform multiple presolve iterations.optional .operations_research.sat.SatParameters.MaxSatAssumptionOrder max_sat_assumption_order = 51 [default = DEFAULT_ASSUMPTION_ORDER];setMaxSatReverseAssumptionOrder(boolean value) If true, adds the assumption in the reverse order of the one defined by max_sat_assumption_order.optional .operations_research.sat.SatParameters.MaxSatStratificationAlgorithm max_sat_stratification = 53 [default = STRATIFICATION_DESCENT];Create one literal for each disjunction of two pairs of tasks.setMaxTimeInSeconds(double value) Maximum time allowed in seconds to solve a problem.setMaxVariableActivityValue(double value) optional double max_variable_activity_value = 16 [default = 1e+100];setMergeAtMostOneWorkLimit(double value) optional double merge_at_most_one_work_limit = 146 [default = 100000000];setMergeNoOverlapWorkLimit(double value) During presolve, we use a maximum clique heuristic to merge together no-overlap constraints or at most one constraints.optional .operations_research.sat.SatParameters.ConflictMinimizationAlgorithm minimization_algorithm = 4 [default = RECURSIVE];setMinimizeReductionDuringPbResolution(boolean value) A different algorithm during PB resolution.setMinimizeSharedClauses(boolean value) Minimize and detect subsumption of shared clauses immediately after they are imported.setMinOrthogonalityForLpConstraints(double value) While adding constraints, skip the constraints which have orthogonality less than 'min_orthogonality_for_lp_constraints' with already added constraints during current call.setMipAutomaticallyScaleVariables(boolean value) If true, some continuous variable might be automatically scaled.setMipCheckPrecision(double value) As explained in mip_precision and mip_max_activity_exponent, we cannot always reach the wanted precision during scaling.setMipComputeTrueObjectiveBound(boolean value) Even if we make big error when scaling the objective, we can always derive a correct lower bound on the original objective by using the exact lower bound on the scaled integer version of the objective.setMipDropTolerance(double value) Any value in the input mip with a magnitude lower than this will be set to zero.setMipMaxActivityExponent(int value) To avoid integer overflow, we always force the maximum possible constraint activity (and objective value) according to the initial variable domain to be smaller than 2 to this given power.setMipMaxBound(double value) We need to bound the maximum magnitude of the variables for CP-SAT, and that is the bound we use.setMipMaxValidMagnitude(double value) Any finite values in the input MIP must be below this threshold, otherwise the model will be reported invalid.setMipPresolveLevel(int value) When solving a MIP, we do some basic floating point presolving before scaling the problem to integer to be handled by CP-SAT.setMipScaleLargeDomain(boolean value) If this is false, then mip_var_scaling is only applied to variables with "small" domain.setMipTreatHighMagnitudeBoundsAsInfinity(boolean value) By default, any variable/constraint bound with a finite value and a magnitude greater than the mip_max_valid_magnitude will result with a invalid model.setMipVarScaling(double value) All continuous variable of the problem will be multiplied by this factor.setMipWantedPrecision(double value) When scaling constraint with double coefficients to integer coefficients, we will multiply by a power of 2 and round the coefficients.In some context, like in a portfolio of search, it makes sense to name a given parameters set for logging purpose.setNameBytes(com.google.protobuf.ByteString value) In some context, like in a portfolio of search, it makes sense to name a given parameters set for logging purpose.setNewConstraintsBatchSize(int value) Add that many lazy constraints (or cuts) at once in the LP.setNewLinearPropagation(boolean value) The new linear propagation code treat all constraints at once and use an adaptation of Bellman-Ford-Tarjan to propagate constraint in a smarter order and potentially detect propagation cycle earlier.setNoOverlap2DBooleanRelationsLimit(int value) If less than this number of boxes are present in a no-overlap 2d, we create 4 Booleans per pair of boxes: - Box 2 is after Box 1 on x. - Box 1 is after Box 2 on x. - Box 2 is after Box 1 on y. - Box 1 is after Box 2 on y.setNumConflictsBeforeStrategyChanges(int value) After each restart, if the number of conflict since the last strategy change is greater that this, then we increment a "strategy_counter" that can be use to change the search strategy used by the following restarts.setNumFullSubsolvers(int value) We distinguish subsolvers that consume a full thread, and the ones that are always interleaved.setNumSearchWorkers(int value) optional int32 num_search_workers = 100 [default = 0];setNumViolationLs(int value) This will create incomplete subsolvers (that are not LNS subsolvers) that use the feasibility jump code to find improving solution, treating the objective improvement as a hard constraint.setNumWorkers(int value) Specify the number of parallel workers (i.e. threads) to use during search.setOnlyAddCutsAtLevelZero(boolean value) For the cut that can be generated at any level, this control if we only try to generate them at the root node.setOnlySolveIp(boolean value) If one try to solve a MIP model with CP-SAT, because we assume all variable to be integer after scaling, we will not necessarily have the correct optimal.setOptimizeWithCore(boolean value) The default optimization method is a simple "linear scan", each time trying to find a better solution than the previous one.setOptimizeWithLbTreeSearch(boolean value) Do a more conventional tree search (by opposition to SAT based one) where we keep all the explored node in a tree.setOptimizeWithMaxHs(boolean value) This has no effect if optimize_with_core is false.setOutputDratProof(boolean value) If true, a DRAT proof that all the clauses inferred by the solver are valid is output to a file.setOutputLratProof(boolean value) If true, an LRAT proof that all the clauses inferred by the solver are valid is output to several files (one for presolve -- reduced to trivial simplifications if cp_model_presolve is false, one per worker, and one for the merged proof).setPbCleanupIncrement(int value) Same as for the clauses, but for the learned pseudo-Boolean constraints.setPbCleanupRatio(double value) optional double pb_cleanup_ratio = 47 [default = 0.5];setPermutePresolveConstraintOrder(boolean value) optional bool permute_presolve_constraint_order = 179 [default = false];setPermuteVariableRandomly(boolean value) This is mainly here to test the solver variability.setPolarityExploitLsHints(boolean value) If true and we have first solution LS workers, tries in some phase to follow a LS solutions that violates has litle constraints as possible.setPolarityRephaseIncrement(int value) If non-zero, then we change the polarity heuristic after that many number of conflicts in an arithmetically increasing fashion.setPolishLpSolution(boolean value) Whether we try to do a few degenerate iteration at the end of an LP solve to minimize the fractionality of the integer variable in the basis.optional .operations_research.sat.SatParameters.VariableOrder preferred_variable_order = 1 [default = IN_ORDER];setPresolveBlockedClause(boolean value) Whether we use an heuristic to detect some basic case of blocked clause in the SAT presolve.setPresolveBvaThreshold(int value) Apply Bounded Variable Addition (BVA) if the number of clauses is reduced by stricly more than this threshold.setPresolveBveClauseWeight(int value) During presolve, we apply BVE only if this weight times the number of clauses plus the number of clause literals is not increased.setPresolveBveThreshold(int value) During presolve, only try to perform the bounded variable elimination (BVE) of a variable x if the number of occurrences of x times the number of occurrences of not(x) is not greater than this parameter.setPresolveExtractIntegerEnforcement(boolean value) If true, we will extract from linear constraints, enforcement literals of the form "integer variable at bound => simplified constraint".setPresolveInclusionWorkLimit(long value) A few presolve operations involve detecting constraints included in other constraint.setPresolveProbingDeterministicTimeLimit(double value) optional double presolve_probing_deterministic_time_limit = 57 [default = 30];setPresolveSubstitutionLevel(int value) How much substitution (also called free variable aggregation in MIP litterature) should we perform at presolve.setPresolveUseBva(boolean value) Whether or not we use Bounded Variable Addition (BVA) in the presolve.setProbingDeterministicTimeLimit(double value) The maximum "deterministic" time limit to spend in probing.setProbingNumCombinationsLimit(int value) How many combinations of pairs or triplets of variables we want to scan.setPropagationLoopDetectionFactor(double value) Some search decisions might cause a really large number of propagations to happen when integer variables with large domains are only reduced by 1 at each step.setPseudoCostReliabilityThreshold(long value) The solver ignores the pseudo costs of variables with number of recordings less than this threshold.setPushAllTasksTowardStart(boolean value) Experimental code: specify if the objective pushes all tasks toward the start of the schedule.setRandomBranchesRatio(double value) A number between 0 and 1 that indicates the proportion of branching variables that are selected randomly instead of choosing the first variable from the given variable_ordering strategy.setRandomizeSearch(boolean value) Randomize fixed search.setRandomPolarityRatio(double value) The proportion of polarity chosen at random.setRandomSeed(int value) At the beginning of each solve, the random number generator used in some part of the solver is reinitialized to this seed.setRelativeGapLimit(double value) optional double relative_gap_limit = 160 [default = 0];setRemoveFixedVariablesEarly(boolean value) If cp_model_presolve is true and there is a large proportion of fixed variable after the first model copy, remap all the model to a dense set of variable before the full presolve even starts.setRepairHint(boolean value) If true, the solver tries to repair the solution given in the hint.setRestartAlgorithms(int index, SatParameters.RestartAlgorithm value) The restart strategies will change each time the strategy_counter is increased.setRestartDlAverageRatio(double value) In the moving average restart algorithms, a restart is triggered if the window average times this ratio is greater that the global average.setRestartLbdAverageRatio(double value) optional double restart_lbd_average_ratio = 71 [default = 1];setRestartPeriod(int value) Restart period for the FIXED_RESTART strategy.setRestartRunningWindowSize(int value) Size of the window for the moving average restarts.setRootLpIterations(int value) Even at the root node, we do not want to spend too much time on the LP if it is "difficult".setRoutingCutDpEffort(double value) The amount of "effort" to spend in dynamic programming for computing routing cuts.setRoutingCutMaxInfeasiblePathLength(int value) If the length of an infeasible path is less than this value, a cut will be added to exclude it.If the size of a subset of nodes of a RoutesConstraint is less than this value, use linear constraints of size 1 and 2 (such as capacity and time window constraints) enforced by the arc literals to compute cuts for this subset (unless the subset size is less than routing_cut_subset_size_for_tight_binary_relation_bound, in which case the corresponding algorithm is used instead).Similar to above, but with an even stronger algorithm in O(n!).setRoutingCutSubsetSizeForShortestPathsBound(int value) Similar to routing_cut_subset_size_for_exact_binary_relation_bound but use a bound based on shortest path distances (which respect triangular inequality).Similar to above, but with a different algorithm producing better cuts, at the price of a higher O(2^n) complexity, where n is the subset size.setSaveLpBasisInLbTreeSearch(boolean value) Experimental.optional .operations_research.sat.SatParameters.SearchBranching search_branching = 82 [default = AUTOMATIC_SEARCH];setSearchRandomVariablePoolSize(long value) Search randomization will collect the top 'search_random_variable_pool_size' valued variables, and pick one randomly.setShareBinaryClauses(boolean value) Allows sharing of new learned binary clause between workers.setSharedTreeBalanceTolerance(int value) How much deeper compared to the ideal max depth of the tree is considered "balanced" enough to still accept a split.setSharedTreeMaxNodesPerWorker(int value) In order to limit total shared memory and communication overhead, limit the total number of nodes that may be generated in the shared tree.setSharedTreeNumWorkers(int value) Enables shared tree search.setSharedTreeOpenLeavesPerWorker(double value) How many open leaf nodes should the shared tree maintain per worker.setSharedTreeSplitMinDtime(double value) How much dtime a worker will wait between proposing splits.optional .operations_research.sat.SatParameters.SharedTreeSplitStrategy shared_tree_split_strategy = 239 [default = SPLIT_STRATEGY_AUTO];setSharedTreeWorkerEnablePhaseSharing(boolean value) If true, shared tree workers share their target phase when returning an assigned subtree for the next worker to use.setSharedTreeWorkerEnableTrailSharing(boolean value) If true, workers share more of the information from their local trail.setSharedTreeWorkerMinRestartsPerSubtree(int value) Minimum restarts before a worker will replace a subtree that looks "bad" based on the average LBD of learned clauses.setShareGlueClauses(boolean value) Allows sharing of short glue clauses between workers.setShareGlueClausesDtime(double value) The amount of dtime between each export of shared glue clauses.setShareLevelZeroBounds(boolean value) Allows sharing of the bounds of modified variables at level 0.setShareLinear2Bounds(boolean value) Allows sharing of the bounds on linear2 discovered at level 0.setShareObjectiveBounds(boolean value) Allows objective sharing between workers.setShavingDeterministicTimeInProbingSearch(double value) Add a shaving phase (where the solver tries to prove that the lower or upper bound of a variable are infeasible) to the probing searchsetShavingSearchDeterministicTime(double value) Specifies the amount of deterministic time spent of each try at shaving a bound in the shaving search.setShavingSearchThreshold(long value) Specifies the threshold between two modes in the shaving procedure.setSolutionPoolDiversityLimit(int value) If solution_pool_size is <= this, we will use DP to keep a "diverse" set of solutions (the one further apart via hamming distance) in the pool.setSolutionPoolSize(int value) Size of the top-n different solutions kept by the solver.setStopAfterFirstSolution(boolean value) For an optimization problem, stop the solver as soon as we have a solution.setStopAfterPresolve(boolean value) Mainly used when improving the presolver.setStopAfterRootPropagation(boolean value) optional bool stop_after_root_propagation = 252 [default = false];setStrategyChangeIncreaseRatio(double value) The parameter num_conflicts_before_strategy_changes is increased by that much after each strategy change.setSubsolverParams(int index, SatParameters value) It is possible to specify additional subsolver configuration.setSubsolverParams(int index, SatParameters.Builder builderForValue) It is possible to specify additional subsolver configuration.setSubsolvers(int index, String value) In multi-thread, the solver can be mainly seen as a portfolio of solvers with different parameters.setSubsumeDuringVivification(boolean value) If we remove clause that we now are "implied" by others.setSubsumptionDuringConflictAnalysis(boolean value) At a really low cost, during the 1-UIP conflict computation, it is easy to detect if some of the involved reasons are subsumed by the current conflict.setSymmetryDetectionDeterministicTimeLimit(double value) Deterministic time limit for symmetry detection.setSymmetryLevel(int value) Whether we try to automatically detect the symmetries in a model and exploit them.setTableCompressionLevel(int value) How much we try to "compress" a table constraint.setTransitivePrecedencesWorkLimit(int value) At root level, we might compute the transitive closure of "precedences" relations so that we can exploit that in scheduling problems.setUseAbslRandom(boolean value) optional bool use_absl_random = 180 [default = false];setUseAllDifferentForCircuit(boolean value) Turn on extra propagation for the circuit constraint.setUseAreaEnergeticReasoningInNoOverlap2D(boolean value) When this is true, the no_overlap_2d constraint is reinforced with an energetic reasoning that uses an area-based energy.setUseBlockingRestart(boolean value) Block a moving restart algorithm if the trail size of the current conflict is greater than the multiplier times the moving average of the trail size at the previous conflicts.setUseChronologicalBacktracking(boolean value) If true, try to backtrack as little as possible on conflict and re-imply the clauses later.setUseCombinedNoOverlap(boolean value) This can be beneficial if there is a lot of no-overlap constraints but a relatively low number of different intervals in the problem.setUseConservativeScaleOverloadChecker(boolean value) Enable a heuristic to solve cumulative constraints using a modified energy constraint.setUseDisjunctiveConstraintInCumulative(boolean value) When this is true, the cumulative constraint is reinforced with propagators from the disjunctive constraint to improve the inference on a set of tasks that are disjunctive at the root of the problem.setUseDualSchedulingHeuristics(boolean value) When set, it activates a few scheduling parameters to improve the lower bound of scheduling problems.setUseDynamicPrecedenceInCumulative(boolean value) optional bool use_dynamic_precedence_in_cumulative = 268 [default = false];setUseDynamicPrecedenceInDisjunctive(boolean value) Whether we try to branch on decision "interval A before interval B" rather than on intervals bounds.setUseEnergeticReasoningInNoOverlap2D(boolean value) When this is true, the no_overlap_2d constraint is reinforced with energetic reasoning.setUseErwaHeuristic(boolean value) Whether we use the ERWA (Exponential Recency Weighted Average) heuristic as described in "Learning Rate Based Branching Heuristic for SAT solvers", J.H.Liang, V.setUseExactLpReason(boolean value) The solver usually exploit the LP relaxation of a model.setUseExtendedProbing(boolean value) Use extended probing (probe bool_or, at_most_one, exactly_one).setUseFeasibilityJump(boolean value) Parameters for an heuristic similar to the one described in the paper: "Feasibility Jump: an LP-free Lagrangian MIP heuristic", Bjørnar Luteberget, Giorgio Sartor, 2023, Mathematical Programming Computation.setUseFeasibilityPump(boolean value) Adds a feasibility pump subsolver along with lns subsolvers.setUseHardPrecedencesInCumulative(boolean value) If true, detect and create constraint for integer variable that are "after" a set of intervals in the same cumulative constraint.setUseImpliedBounds(boolean value) Stores and exploits "implied-bounds" in the solver.setUseLbRelaxLns(boolean value) Turns on neighborhood generator based on local branching LP.setUseLinear3ForNoOverlap2DPrecedences(boolean value) When set, this activates a propagator for the no_overlap_2d constraint that uses any eventual linear constraints of the model in the form `{start interval 1} - {end interval 2} + c*w <= ub` to detect that two intervals must overlap in one dimension for some values of `w`.setUseLns(boolean value) Testing parameters used to disable all lns workers.setUseLnsOnly(boolean value) Experimental parameters to disable everything but lns.setUseLsOnly(boolean value) Disable every other type of subsolver, setting this turns CP-SAT into a pure local-search solver.setUseNewIntegerConflictResolution(boolean value) This should be better on integer problems.setUseObjectiveLbSearch(boolean value) If true, search will search in ascending max objective value (when minimizing) starting from the lower bound of the objective.setUseObjectiveShavingSearch(boolean value) This search differs from the previous search as it will not use assumptions to bound the objective, and it will recreate a full model with the hardcoded objective value.setUseOptimizationHints(boolean value) For an optimization problem, whether we follow some hints in order to find a better first solution.setUseOptionalVariables(boolean value) If true, we automatically detect variables whose constraint are always enforced by the same literal and we mark them as optional.setUseOverloadCheckerInCumulative(boolean value) When this is true, the cumulative constraint is reinforced with overload checking, i.e., an additional level of reasoning based on energy.setUsePbResolution(boolean value) Experimental.setUsePhaseSaving(boolean value) If this is true, then the polarity of a variable will be the last value it was assigned to, or its default polarity if it was never assigned since the call to ResetDecisionHeuristic().setUsePrecedencesInDisjunctiveConstraint(boolean value) When this is true, then a disjunctive constraint will try to use the precedence relations between time intervals to propagate their bounds further.setUseProbingSearch(boolean value) If true, search will continuously probe Boolean variables, and integer variable bounds.setUseRinsLns(boolean value) Turns on relaxation induced neighborhood generator.setUseSatInprocessing(boolean value) Enable or disable "inprocessing" which is some SAT presolving done at each restart to the root level.setUseSharedTreeSearch(boolean value) Set on shared subtree workers.setUseStrongPropagationInDisjunctive(boolean value) Enable stronger and more expensive propagation on no_overlap constraint.setUseSymmetryInLp(boolean value) When we have symmetry, it is possible to "fold" all variables from the same orbit into a single variable, while having the same power of LP relaxation.setUseTimetableEdgeFindingInCumulative(boolean value) When this is true, the cumulative constraint is reinforced with timetable edge finding, i.e., an additional level of reasoning based on the conjunction of energy and mandatory parts.setUseTimetablingInNoOverlap2D(boolean value) When this is true, the no_overlap_2d constraint is reinforced with propagators from the cumulative constraints.setUseTryEdgeReasoningInNoOverlap2D(boolean value) optional bool use_try_edge_reasoning_in_no_overlap_2d = 299 [default = false];setVariableActivityDecay(double value) Each time a conflict is found, the activities of some variables are increased by one.setVariablesShavingLevel(int value) This search takes all Boolean or integer variables, and maximize or minimize them in order to reduce their domain. -1 is automatic, otherwise value 0 disables it, and 1, 2, or 3 changes something.setViolationLsCompoundMoveProbability(double value) Probability of using compound move search each restart.setViolationLsPerturbationPeriod(int value) How long violation_ls should wait before perturbating a solution.Methods inherited from class com.google.protobuf.GeneratedMessage.Builder
addRepeatedField, clearField, clearOneof, clone, getAllFields, getField, getFieldBuilder, getOneofFieldDescriptor, getParentForChildren, getRepeatedField, getRepeatedFieldBuilder, getRepeatedFieldCount, getUnknownFields, getUnknownFieldSetBuilder, hasField, hasOneof, internalGetMapField, internalGetMapFieldReflection, internalGetMutableMapField, internalGetMutableMapFieldReflection, isClean, markClean, mergeUnknownFields, mergeUnknownLengthDelimitedField, mergeUnknownVarintField, newBuilderForField, onBuilt, onChanged, parseUnknownField, setField, setRepeatedField, setUnknownFields, setUnknownFieldSetBuilder, setUnknownFieldsProto3Methods inherited from class com.google.protobuf.AbstractMessage.Builder
findInitializationErrors, getInitializationErrorString, internalMergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, newUninitializedMessageException, toStringMethods inherited from class com.google.protobuf.AbstractMessageLite.Builder
addAll, addAll, mergeDelimitedFrom, mergeDelimitedFrom, mergeFrom, newUninitializedMessageExceptionMethods inherited from class Object
equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, waitMethods inherited from interface com.google.protobuf.Message.Builder
mergeDelimitedFrom, mergeDelimitedFromMethods inherited from interface com.google.protobuf.MessageLite.Builder
mergeFromMethods inherited from interface com.google.protobuf.MessageOrBuilder
findInitializationErrors, getAllFields, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof
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Method Details
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getDescriptor
public static final com.google.protobuf.Descriptors.Descriptor getDescriptor() -
internalGetFieldAccessorTable
protected com.google.protobuf.GeneratedMessage.FieldAccessorTable internalGetFieldAccessorTable()- Specified by:
internalGetFieldAccessorTablein classcom.google.protobuf.GeneratedMessage.Builder<SatParameters.Builder>
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clear
- Specified by:
clearin interfacecom.google.protobuf.Message.Builder- Specified by:
clearin interfacecom.google.protobuf.MessageLite.Builder- Overrides:
clearin classcom.google.protobuf.GeneratedMessage.Builder<SatParameters.Builder>
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getDescriptorForType
public com.google.protobuf.Descriptors.Descriptor getDescriptorForType()- Specified by:
getDescriptorForTypein interfacecom.google.protobuf.Message.Builder- Specified by:
getDescriptorForTypein interfacecom.google.protobuf.MessageOrBuilder- Overrides:
getDescriptorForTypein classcom.google.protobuf.GeneratedMessage.Builder<SatParameters.Builder>
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getDefaultInstanceForType
- Specified by:
getDefaultInstanceForTypein interfacecom.google.protobuf.MessageLiteOrBuilder- Specified by:
getDefaultInstanceForTypein interfacecom.google.protobuf.MessageOrBuilder
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build
- Specified by:
buildin interfacecom.google.protobuf.Message.Builder- Specified by:
buildin interfacecom.google.protobuf.MessageLite.Builder
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buildPartial
- Specified by:
buildPartialin interfacecom.google.protobuf.Message.Builder- Specified by:
buildPartialin interfacecom.google.protobuf.MessageLite.Builder
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mergeFrom
- Specified by:
mergeFromin interfacecom.google.protobuf.Message.Builder- Overrides:
mergeFromin classcom.google.protobuf.AbstractMessage.Builder<SatParameters.Builder>
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mergeFrom
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isInitialized
public final boolean isInitialized()- Specified by:
isInitializedin interfacecom.google.protobuf.MessageLiteOrBuilder- Overrides:
isInitializedin classcom.google.protobuf.GeneratedMessage.Builder<SatParameters.Builder>
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mergeFrom
public SatParameters.Builder mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException - Specified by:
mergeFromin interfacecom.google.protobuf.Message.Builder- Specified by:
mergeFromin interfacecom.google.protobuf.MessageLite.Builder- Overrides:
mergeFromin classcom.google.protobuf.AbstractMessage.Builder<SatParameters.Builder>- Throws:
IOException
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hasName
public boolean hasName()In some context, like in a portfolio of search, it makes sense to name a given parameters set for logging purpose.
optional string name = 171 [default = ""];- Specified by:
hasNamein interfaceSatParametersOrBuilder- Returns:
- Whether the name field is set.
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getName
In some context, like in a portfolio of search, it makes sense to name a given parameters set for logging purpose.
optional string name = 171 [default = ""];- Specified by:
getNamein interfaceSatParametersOrBuilder- Returns:
- The name.
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getNameBytes
public com.google.protobuf.ByteString getNameBytes()In some context, like in a portfolio of search, it makes sense to name a given parameters set for logging purpose.
optional string name = 171 [default = ""];- Specified by:
getNameBytesin interfaceSatParametersOrBuilder- Returns:
- The bytes for name.
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setName
In some context, like in a portfolio of search, it makes sense to name a given parameters set for logging purpose.
optional string name = 171 [default = ""];- Parameters:
value- The name to set.- Returns:
- This builder for chaining.
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clearName
In some context, like in a portfolio of search, it makes sense to name a given parameters set for logging purpose.
optional string name = 171 [default = ""];- Returns:
- This builder for chaining.
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setNameBytes
In some context, like in a portfolio of search, it makes sense to name a given parameters set for logging purpose.
optional string name = 171 [default = ""];- Parameters:
value- The bytes for name to set.- Returns:
- This builder for chaining.
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hasPreferredVariableOrder
public boolean hasPreferredVariableOrder()optional .operations_research.sat.SatParameters.VariableOrder preferred_variable_order = 1 [default = IN_ORDER];- Specified by:
hasPreferredVariableOrderin interfaceSatParametersOrBuilder- Returns:
- Whether the preferredVariableOrder field is set.
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getPreferredVariableOrder
optional .operations_research.sat.SatParameters.VariableOrder preferred_variable_order = 1 [default = IN_ORDER];- Specified by:
getPreferredVariableOrderin interfaceSatParametersOrBuilder- Returns:
- The preferredVariableOrder.
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setPreferredVariableOrder
optional .operations_research.sat.SatParameters.VariableOrder preferred_variable_order = 1 [default = IN_ORDER];- Parameters:
value- The preferredVariableOrder to set.- Returns:
- This builder for chaining.
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clearPreferredVariableOrder
optional .operations_research.sat.SatParameters.VariableOrder preferred_variable_order = 1 [default = IN_ORDER];- Returns:
- This builder for chaining.
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hasInitialPolarity
public boolean hasInitialPolarity()optional .operations_research.sat.SatParameters.Polarity initial_polarity = 2 [default = POLARITY_FALSE];- Specified by:
hasInitialPolarityin interfaceSatParametersOrBuilder- Returns:
- Whether the initialPolarity field is set.
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getInitialPolarity
optional .operations_research.sat.SatParameters.Polarity initial_polarity = 2 [default = POLARITY_FALSE];- Specified by:
getInitialPolarityin interfaceSatParametersOrBuilder- Returns:
- The initialPolarity.
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setInitialPolarity
optional .operations_research.sat.SatParameters.Polarity initial_polarity = 2 [default = POLARITY_FALSE];- Parameters:
value- The initialPolarity to set.- Returns:
- This builder for chaining.
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clearInitialPolarity
optional .operations_research.sat.SatParameters.Polarity initial_polarity = 2 [default = POLARITY_FALSE];- Returns:
- This builder for chaining.
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hasUsePhaseSaving
public boolean hasUsePhaseSaving()If this is true, then the polarity of a variable will be the last value it was assigned to, or its default polarity if it was never assigned since the call to ResetDecisionHeuristic(). Actually, we use a newer version where we follow the last value in the longest non-conflicting partial assignment in the current phase. This is called 'literal phase saving'. For details see 'A Lightweight Component Caching Scheme for Satisfiability Solvers' K. Pipatsrisawat and A.Darwiche, In 10th International Conference on Theory and Applications of Satisfiability Testing, 2007.
optional bool use_phase_saving = 44 [default = true];- Specified by:
hasUsePhaseSavingin interfaceSatParametersOrBuilder- Returns:
- Whether the usePhaseSaving field is set.
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getUsePhaseSaving
public boolean getUsePhaseSaving()If this is true, then the polarity of a variable will be the last value it was assigned to, or its default polarity if it was never assigned since the call to ResetDecisionHeuristic(). Actually, we use a newer version where we follow the last value in the longest non-conflicting partial assignment in the current phase. This is called 'literal phase saving'. For details see 'A Lightweight Component Caching Scheme for Satisfiability Solvers' K. Pipatsrisawat and A.Darwiche, In 10th International Conference on Theory and Applications of Satisfiability Testing, 2007.
optional bool use_phase_saving = 44 [default = true];- Specified by:
getUsePhaseSavingin interfaceSatParametersOrBuilder- Returns:
- The usePhaseSaving.
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setUsePhaseSaving
If this is true, then the polarity of a variable will be the last value it was assigned to, or its default polarity if it was never assigned since the call to ResetDecisionHeuristic(). Actually, we use a newer version where we follow the last value in the longest non-conflicting partial assignment in the current phase. This is called 'literal phase saving'. For details see 'A Lightweight Component Caching Scheme for Satisfiability Solvers' K. Pipatsrisawat and A.Darwiche, In 10th International Conference on Theory and Applications of Satisfiability Testing, 2007.
optional bool use_phase_saving = 44 [default = true];- Parameters:
value- The usePhaseSaving to set.- Returns:
- This builder for chaining.
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clearUsePhaseSaving
If this is true, then the polarity of a variable will be the last value it was assigned to, or its default polarity if it was never assigned since the call to ResetDecisionHeuristic(). Actually, we use a newer version where we follow the last value in the longest non-conflicting partial assignment in the current phase. This is called 'literal phase saving'. For details see 'A Lightweight Component Caching Scheme for Satisfiability Solvers' K. Pipatsrisawat and A.Darwiche, In 10th International Conference on Theory and Applications of Satisfiability Testing, 2007.
optional bool use_phase_saving = 44 [default = true];- Returns:
- This builder for chaining.
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hasPolarityRephaseIncrement
public boolean hasPolarityRephaseIncrement()If non-zero, then we change the polarity heuristic after that many number of conflicts in an arithmetically increasing fashion. So x the first time, 2 * x the second time, etc...
optional int32 polarity_rephase_increment = 168 [default = 1000];- Specified by:
hasPolarityRephaseIncrementin interfaceSatParametersOrBuilder- Returns:
- Whether the polarityRephaseIncrement field is set.
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getPolarityRephaseIncrement
public int getPolarityRephaseIncrement()If non-zero, then we change the polarity heuristic after that many number of conflicts in an arithmetically increasing fashion. So x the first time, 2 * x the second time, etc...
optional int32 polarity_rephase_increment = 168 [default = 1000];- Specified by:
getPolarityRephaseIncrementin interfaceSatParametersOrBuilder- Returns:
- The polarityRephaseIncrement.
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setPolarityRephaseIncrement
If non-zero, then we change the polarity heuristic after that many number of conflicts in an arithmetically increasing fashion. So x the first time, 2 * x the second time, etc...
optional int32 polarity_rephase_increment = 168 [default = 1000];- Parameters:
value- The polarityRephaseIncrement to set.- Returns:
- This builder for chaining.
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clearPolarityRephaseIncrement
If non-zero, then we change the polarity heuristic after that many number of conflicts in an arithmetically increasing fashion. So x the first time, 2 * x the second time, etc...
optional int32 polarity_rephase_increment = 168 [default = 1000];- Returns:
- This builder for chaining.
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hasPolarityExploitLsHints
public boolean hasPolarityExploitLsHints()If true and we have first solution LS workers, tries in some phase to follow a LS solutions that violates has litle constraints as possible.
optional bool polarity_exploit_ls_hints = 309 [default = false];- Specified by:
hasPolarityExploitLsHintsin interfaceSatParametersOrBuilder- Returns:
- Whether the polarityExploitLsHints field is set.
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getPolarityExploitLsHints
public boolean getPolarityExploitLsHints()If true and we have first solution LS workers, tries in some phase to follow a LS solutions that violates has litle constraints as possible.
optional bool polarity_exploit_ls_hints = 309 [default = false];- Specified by:
getPolarityExploitLsHintsin interfaceSatParametersOrBuilder- Returns:
- The polarityExploitLsHints.
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setPolarityExploitLsHints
If true and we have first solution LS workers, tries in some phase to follow a LS solutions that violates has litle constraints as possible.
optional bool polarity_exploit_ls_hints = 309 [default = false];- Parameters:
value- The polarityExploitLsHints to set.- Returns:
- This builder for chaining.
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clearPolarityExploitLsHints
If true and we have first solution LS workers, tries in some phase to follow a LS solutions that violates has litle constraints as possible.
optional bool polarity_exploit_ls_hints = 309 [default = false];- Returns:
- This builder for chaining.
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hasRandomPolarityRatio
public boolean hasRandomPolarityRatio()The proportion of polarity chosen at random. Note that this take precedence over the phase saving heuristic. This is different from initial_polarity:POLARITY_RANDOM because it will select a new random polarity each time the variable is branched upon instead of selecting one initially and then always taking this choice.
optional double random_polarity_ratio = 45 [default = 0];- Specified by:
hasRandomPolarityRatioin interfaceSatParametersOrBuilder- Returns:
- Whether the randomPolarityRatio field is set.
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getRandomPolarityRatio
public double getRandomPolarityRatio()The proportion of polarity chosen at random. Note that this take precedence over the phase saving heuristic. This is different from initial_polarity:POLARITY_RANDOM because it will select a new random polarity each time the variable is branched upon instead of selecting one initially and then always taking this choice.
optional double random_polarity_ratio = 45 [default = 0];- Specified by:
getRandomPolarityRatioin interfaceSatParametersOrBuilder- Returns:
- The randomPolarityRatio.
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setRandomPolarityRatio
The proportion of polarity chosen at random. Note that this take precedence over the phase saving heuristic. This is different from initial_polarity:POLARITY_RANDOM because it will select a new random polarity each time the variable is branched upon instead of selecting one initially and then always taking this choice.
optional double random_polarity_ratio = 45 [default = 0];- Parameters:
value- The randomPolarityRatio to set.- Returns:
- This builder for chaining.
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clearRandomPolarityRatio
The proportion of polarity chosen at random. Note that this take precedence over the phase saving heuristic. This is different from initial_polarity:POLARITY_RANDOM because it will select a new random polarity each time the variable is branched upon instead of selecting one initially and then always taking this choice.
optional double random_polarity_ratio = 45 [default = 0];- Returns:
- This builder for chaining.
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hasRandomBranchesRatio
public boolean hasRandomBranchesRatio()A number between 0 and 1 that indicates the proportion of branching variables that are selected randomly instead of choosing the first variable from the given variable_ordering strategy.
optional double random_branches_ratio = 32 [default = 0];- Specified by:
hasRandomBranchesRatioin interfaceSatParametersOrBuilder- Returns:
- Whether the randomBranchesRatio field is set.
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getRandomBranchesRatio
public double getRandomBranchesRatio()A number between 0 and 1 that indicates the proportion of branching variables that are selected randomly instead of choosing the first variable from the given variable_ordering strategy.
optional double random_branches_ratio = 32 [default = 0];- Specified by:
getRandomBranchesRatioin interfaceSatParametersOrBuilder- Returns:
- The randomBranchesRatio.
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setRandomBranchesRatio
A number between 0 and 1 that indicates the proportion of branching variables that are selected randomly instead of choosing the first variable from the given variable_ordering strategy.
optional double random_branches_ratio = 32 [default = 0];- Parameters:
value- The randomBranchesRatio to set.- Returns:
- This builder for chaining.
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clearRandomBranchesRatio
A number between 0 and 1 that indicates the proportion of branching variables that are selected randomly instead of choosing the first variable from the given variable_ordering strategy.
optional double random_branches_ratio = 32 [default = 0];- Returns:
- This builder for chaining.
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hasUseErwaHeuristic
public boolean hasUseErwaHeuristic()Whether we use the ERWA (Exponential Recency Weighted Average) heuristic as described in "Learning Rate Based Branching Heuristic for SAT solvers", J.H.Liang, V. Ganesh, P. Poupart, K.Czarnecki, SAT 2016.
optional bool use_erwa_heuristic = 75 [default = false];- Specified by:
hasUseErwaHeuristicin interfaceSatParametersOrBuilder- Returns:
- Whether the useErwaHeuristic field is set.
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getUseErwaHeuristic
public boolean getUseErwaHeuristic()Whether we use the ERWA (Exponential Recency Weighted Average) heuristic as described in "Learning Rate Based Branching Heuristic for SAT solvers", J.H.Liang, V. Ganesh, P. Poupart, K.Czarnecki, SAT 2016.
optional bool use_erwa_heuristic = 75 [default = false];- Specified by:
getUseErwaHeuristicin interfaceSatParametersOrBuilder- Returns:
- The useErwaHeuristic.
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setUseErwaHeuristic
Whether we use the ERWA (Exponential Recency Weighted Average) heuristic as described in "Learning Rate Based Branching Heuristic for SAT solvers", J.H.Liang, V. Ganesh, P. Poupart, K.Czarnecki, SAT 2016.
optional bool use_erwa_heuristic = 75 [default = false];- Parameters:
value- The useErwaHeuristic to set.- Returns:
- This builder for chaining.
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clearUseErwaHeuristic
Whether we use the ERWA (Exponential Recency Weighted Average) heuristic as described in "Learning Rate Based Branching Heuristic for SAT solvers", J.H.Liang, V. Ganesh, P. Poupart, K.Czarnecki, SAT 2016.
optional bool use_erwa_heuristic = 75 [default = false];- Returns:
- This builder for chaining.
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hasInitialVariablesActivity
public boolean hasInitialVariablesActivity()The initial value of the variables activity. A non-zero value only make sense when use_erwa_heuristic is true. Experiments with a value of 1e-2 together with the ERWA heuristic showed slighthly better result than simply using zero. The idea is that when the "learning rate" of a variable becomes lower than this value, then we prefer to branch on never explored before variables. This is not in the ERWA paper.
optional double initial_variables_activity = 76 [default = 0];- Specified by:
hasInitialVariablesActivityin interfaceSatParametersOrBuilder- Returns:
- Whether the initialVariablesActivity field is set.
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getInitialVariablesActivity
public double getInitialVariablesActivity()The initial value of the variables activity. A non-zero value only make sense when use_erwa_heuristic is true. Experiments with a value of 1e-2 together with the ERWA heuristic showed slighthly better result than simply using zero. The idea is that when the "learning rate" of a variable becomes lower than this value, then we prefer to branch on never explored before variables. This is not in the ERWA paper.
optional double initial_variables_activity = 76 [default = 0];- Specified by:
getInitialVariablesActivityin interfaceSatParametersOrBuilder- Returns:
- The initialVariablesActivity.
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setInitialVariablesActivity
The initial value of the variables activity. A non-zero value only make sense when use_erwa_heuristic is true. Experiments with a value of 1e-2 together with the ERWA heuristic showed slighthly better result than simply using zero. The idea is that when the "learning rate" of a variable becomes lower than this value, then we prefer to branch on never explored before variables. This is not in the ERWA paper.
optional double initial_variables_activity = 76 [default = 0];- Parameters:
value- The initialVariablesActivity to set.- Returns:
- This builder for chaining.
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clearInitialVariablesActivity
The initial value of the variables activity. A non-zero value only make sense when use_erwa_heuristic is true. Experiments with a value of 1e-2 together with the ERWA heuristic showed slighthly better result than simply using zero. The idea is that when the "learning rate" of a variable becomes lower than this value, then we prefer to branch on never explored before variables. This is not in the ERWA paper.
optional double initial_variables_activity = 76 [default = 0];- Returns:
- This builder for chaining.
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hasAlsoBumpVariablesInConflictReasons
public boolean hasAlsoBumpVariablesInConflictReasons()When this is true, then the variables that appear in any of the reason of the variables in a conflict have their activity bumped. This is addition to the variables in the conflict, and the one that were used during conflict resolution.
optional bool also_bump_variables_in_conflict_reasons = 77 [default = false];- Specified by:
hasAlsoBumpVariablesInConflictReasonsin interfaceSatParametersOrBuilder- Returns:
- Whether the alsoBumpVariablesInConflictReasons field is set.
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getAlsoBumpVariablesInConflictReasons
public boolean getAlsoBumpVariablesInConflictReasons()When this is true, then the variables that appear in any of the reason of the variables in a conflict have their activity bumped. This is addition to the variables in the conflict, and the one that were used during conflict resolution.
optional bool also_bump_variables_in_conflict_reasons = 77 [default = false];- Specified by:
getAlsoBumpVariablesInConflictReasonsin interfaceSatParametersOrBuilder- Returns:
- The alsoBumpVariablesInConflictReasons.
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setAlsoBumpVariablesInConflictReasons
When this is true, then the variables that appear in any of the reason of the variables in a conflict have their activity bumped. This is addition to the variables in the conflict, and the one that were used during conflict resolution.
optional bool also_bump_variables_in_conflict_reasons = 77 [default = false];- Parameters:
value- The alsoBumpVariablesInConflictReasons to set.- Returns:
- This builder for chaining.
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clearAlsoBumpVariablesInConflictReasons
When this is true, then the variables that appear in any of the reason of the variables in a conflict have their activity bumped. This is addition to the variables in the conflict, and the one that were used during conflict resolution.
optional bool also_bump_variables_in_conflict_reasons = 77 [default = false];- Returns:
- This builder for chaining.
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hasMinimizationAlgorithm
public boolean hasMinimizationAlgorithm()optional .operations_research.sat.SatParameters.ConflictMinimizationAlgorithm minimization_algorithm = 4 [default = RECURSIVE];- Specified by:
hasMinimizationAlgorithmin interfaceSatParametersOrBuilder- Returns:
- Whether the minimizationAlgorithm field is set.
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getMinimizationAlgorithm
optional .operations_research.sat.SatParameters.ConflictMinimizationAlgorithm minimization_algorithm = 4 [default = RECURSIVE];- Specified by:
getMinimizationAlgorithmin interfaceSatParametersOrBuilder- Returns:
- The minimizationAlgorithm.
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setMinimizationAlgorithm
public SatParameters.Builder setMinimizationAlgorithm(SatParameters.ConflictMinimizationAlgorithm value) optional .operations_research.sat.SatParameters.ConflictMinimizationAlgorithm minimization_algorithm = 4 [default = RECURSIVE];- Parameters:
value- The minimizationAlgorithm to set.- Returns:
- This builder for chaining.
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clearMinimizationAlgorithm
optional .operations_research.sat.SatParameters.ConflictMinimizationAlgorithm minimization_algorithm = 4 [default = RECURSIVE];- Returns:
- This builder for chaining.
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hasBinaryMinimizationAlgorithm
public boolean hasBinaryMinimizationAlgorithm()optional .operations_research.sat.SatParameters.BinaryMinizationAlgorithm binary_minimization_algorithm = 34 [default = BINARY_MINIMIZATION_FROM_UIP_AND_DECISIONS];- Specified by:
hasBinaryMinimizationAlgorithmin interfaceSatParametersOrBuilder- Returns:
- Whether the binaryMinimizationAlgorithm field is set.
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getBinaryMinimizationAlgorithm
optional .operations_research.sat.SatParameters.BinaryMinizationAlgorithm binary_minimization_algorithm = 34 [default = BINARY_MINIMIZATION_FROM_UIP_AND_DECISIONS];- Specified by:
getBinaryMinimizationAlgorithmin interfaceSatParametersOrBuilder- Returns:
- The binaryMinimizationAlgorithm.
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setBinaryMinimizationAlgorithm
public SatParameters.Builder setBinaryMinimizationAlgorithm(SatParameters.BinaryMinizationAlgorithm value) optional .operations_research.sat.SatParameters.BinaryMinizationAlgorithm binary_minimization_algorithm = 34 [default = BINARY_MINIMIZATION_FROM_UIP_AND_DECISIONS];- Parameters:
value- The binaryMinimizationAlgorithm to set.- Returns:
- This builder for chaining.
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clearBinaryMinimizationAlgorithm
optional .operations_research.sat.SatParameters.BinaryMinizationAlgorithm binary_minimization_algorithm = 34 [default = BINARY_MINIMIZATION_FROM_UIP_AND_DECISIONS];- Returns:
- This builder for chaining.
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hasSubsumptionDuringConflictAnalysis
public boolean hasSubsumptionDuringConflictAnalysis()At a really low cost, during the 1-UIP conflict computation, it is easy to detect if some of the involved reasons are subsumed by the current conflict. When this is true, such clauses are detached and later removed from the problem.
optional bool subsumption_during_conflict_analysis = 56 [default = true];- Specified by:
hasSubsumptionDuringConflictAnalysisin interfaceSatParametersOrBuilder- Returns:
- Whether the subsumptionDuringConflictAnalysis field is set.
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getSubsumptionDuringConflictAnalysis
public boolean getSubsumptionDuringConflictAnalysis()At a really low cost, during the 1-UIP conflict computation, it is easy to detect if some of the involved reasons are subsumed by the current conflict. When this is true, such clauses are detached and later removed from the problem.
optional bool subsumption_during_conflict_analysis = 56 [default = true];- Specified by:
getSubsumptionDuringConflictAnalysisin interfaceSatParametersOrBuilder- Returns:
- The subsumptionDuringConflictAnalysis.
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setSubsumptionDuringConflictAnalysis
At a really low cost, during the 1-UIP conflict computation, it is easy to detect if some of the involved reasons are subsumed by the current conflict. When this is true, such clauses are detached and later removed from the problem.
optional bool subsumption_during_conflict_analysis = 56 [default = true];- Parameters:
value- The subsumptionDuringConflictAnalysis to set.- Returns:
- This builder for chaining.
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clearSubsumptionDuringConflictAnalysis
At a really low cost, during the 1-UIP conflict computation, it is easy to detect if some of the involved reasons are subsumed by the current conflict. When this is true, such clauses are detached and later removed from the problem.
optional bool subsumption_during_conflict_analysis = 56 [default = true];- Returns:
- This builder for chaining.
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hasExtraSubsumptionDuringConflictAnalysis
public boolean hasExtraSubsumptionDuringConflictAnalysis()It is possible that "intermediate" clauses during conflict resolution subsumes some of the clauses that propagated. This is quite cheap to detect and result in more subsumption/strengthening of clauses.
optional bool extra_subsumption_during_conflict_analysis = 351 [default = true];- Specified by:
hasExtraSubsumptionDuringConflictAnalysisin interfaceSatParametersOrBuilder- Returns:
- Whether the extraSubsumptionDuringConflictAnalysis field is set.
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getExtraSubsumptionDuringConflictAnalysis
public boolean getExtraSubsumptionDuringConflictAnalysis()It is possible that "intermediate" clauses during conflict resolution subsumes some of the clauses that propagated. This is quite cheap to detect and result in more subsumption/strengthening of clauses.
optional bool extra_subsumption_during_conflict_analysis = 351 [default = true];- Specified by:
getExtraSubsumptionDuringConflictAnalysisin interfaceSatParametersOrBuilder- Returns:
- The extraSubsumptionDuringConflictAnalysis.
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setExtraSubsumptionDuringConflictAnalysis
It is possible that "intermediate" clauses during conflict resolution subsumes some of the clauses that propagated. This is quite cheap to detect and result in more subsumption/strengthening of clauses.
optional bool extra_subsumption_during_conflict_analysis = 351 [default = true];- Parameters:
value- The extraSubsumptionDuringConflictAnalysis to set.- Returns:
- This builder for chaining.
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clearExtraSubsumptionDuringConflictAnalysis
It is possible that "intermediate" clauses during conflict resolution subsumes some of the clauses that propagated. This is quite cheap to detect and result in more subsumption/strengthening of clauses.
optional bool extra_subsumption_during_conflict_analysis = 351 [default = true];- Returns:
- This builder for chaining.
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hasDecisionSubsumptionDuringConflictAnalysis
public boolean hasDecisionSubsumptionDuringConflictAnalysis()Try even more subsumption options during conflict analysis.
optional bool decision_subsumption_during_conflict_analysis = 353 [default = true];- Specified by:
hasDecisionSubsumptionDuringConflictAnalysisin interfaceSatParametersOrBuilder- Returns:
- Whether the decisionSubsumptionDuringConflictAnalysis field is set.
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getDecisionSubsumptionDuringConflictAnalysis
public boolean getDecisionSubsumptionDuringConflictAnalysis()Try even more subsumption options during conflict analysis.
optional bool decision_subsumption_during_conflict_analysis = 353 [default = true];- Specified by:
getDecisionSubsumptionDuringConflictAnalysisin interfaceSatParametersOrBuilder- Returns:
- The decisionSubsumptionDuringConflictAnalysis.
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setDecisionSubsumptionDuringConflictAnalysis
Try even more subsumption options during conflict analysis.
optional bool decision_subsumption_during_conflict_analysis = 353 [default = true];- Parameters:
value- The decisionSubsumptionDuringConflictAnalysis to set.- Returns:
- This builder for chaining.
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clearDecisionSubsumptionDuringConflictAnalysis
Try even more subsumption options during conflict analysis.
optional bool decision_subsumption_during_conflict_analysis = 353 [default = true];- Returns:
- This builder for chaining.
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hasEagerlySubsumeLastNConflicts
public boolean hasEagerlySubsumeLastNConflicts()If >=0, each time we have a conflict, we try to subsume the last n learned clause with it.
optional int32 eagerly_subsume_last_n_conflicts = 343 [default = 4];- Specified by:
hasEagerlySubsumeLastNConflictsin interfaceSatParametersOrBuilder- Returns:
- Whether the eagerlySubsumeLastNConflicts field is set.
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getEagerlySubsumeLastNConflicts
public int getEagerlySubsumeLastNConflicts()If >=0, each time we have a conflict, we try to subsume the last n learned clause with it.
optional int32 eagerly_subsume_last_n_conflicts = 343 [default = 4];- Specified by:
getEagerlySubsumeLastNConflictsin interfaceSatParametersOrBuilder- Returns:
- The eagerlySubsumeLastNConflicts.
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setEagerlySubsumeLastNConflicts
If >=0, each time we have a conflict, we try to subsume the last n learned clause with it.
optional int32 eagerly_subsume_last_n_conflicts = 343 [default = 4];- Parameters:
value- The eagerlySubsumeLastNConflicts to set.- Returns:
- This builder for chaining.
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clearEagerlySubsumeLastNConflicts
If >=0, each time we have a conflict, we try to subsume the last n learned clause with it.
optional int32 eagerly_subsume_last_n_conflicts = 343 [default = 4];- Returns:
- This builder for chaining.
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hasSubsumeDuringVivification
public boolean hasSubsumeDuringVivification()If we remove clause that we now are "implied" by others. Note that this might not always be good as we might loose some propagation power.
optional bool subsume_during_vivification = 355 [default = true];- Specified by:
hasSubsumeDuringVivificationin interfaceSatParametersOrBuilder- Returns:
- Whether the subsumeDuringVivification field is set.
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getSubsumeDuringVivification
public boolean getSubsumeDuringVivification()If we remove clause that we now are "implied" by others. Note that this might not always be good as we might loose some propagation power.
optional bool subsume_during_vivification = 355 [default = true];- Specified by:
getSubsumeDuringVivificationin interfaceSatParametersOrBuilder- Returns:
- The subsumeDuringVivification.
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setSubsumeDuringVivification
If we remove clause that we now are "implied" by others. Note that this might not always be good as we might loose some propagation power.
optional bool subsume_during_vivification = 355 [default = true];- Parameters:
value- The subsumeDuringVivification to set.- Returns:
- This builder for chaining.
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clearSubsumeDuringVivification
If we remove clause that we now are "implied" by others. Note that this might not always be good as we might loose some propagation power.
optional bool subsume_during_vivification = 355 [default = true];- Returns:
- This builder for chaining.
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hasUseChronologicalBacktracking
public boolean hasUseChronologicalBacktracking()If true, try to backtrack as little as possible on conflict and re-imply the clauses later. This means we discard less propagation than traditional backjumping, but requites additional bookkeeping to handle reimplication. See: https://doi.org/10.1007/978-3-319-94144-8_7
optional bool use_chronological_backtracking = 330 [default = false];- Specified by:
hasUseChronologicalBacktrackingin interfaceSatParametersOrBuilder- Returns:
- Whether the useChronologicalBacktracking field is set.
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getUseChronologicalBacktracking
public boolean getUseChronologicalBacktracking()If true, try to backtrack as little as possible on conflict and re-imply the clauses later. This means we discard less propagation than traditional backjumping, but requites additional bookkeeping to handle reimplication. See: https://doi.org/10.1007/978-3-319-94144-8_7
optional bool use_chronological_backtracking = 330 [default = false];- Specified by:
getUseChronologicalBacktrackingin interfaceSatParametersOrBuilder- Returns:
- The useChronologicalBacktracking.
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setUseChronologicalBacktracking
If true, try to backtrack as little as possible on conflict and re-imply the clauses later. This means we discard less propagation than traditional backjumping, but requites additional bookkeeping to handle reimplication. See: https://doi.org/10.1007/978-3-319-94144-8_7
optional bool use_chronological_backtracking = 330 [default = false];- Parameters:
value- The useChronologicalBacktracking to set.- Returns:
- This builder for chaining.
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clearUseChronologicalBacktracking
If true, try to backtrack as little as possible on conflict and re-imply the clauses later. This means we discard less propagation than traditional backjumping, but requites additional bookkeeping to handle reimplication. See: https://doi.org/10.1007/978-3-319-94144-8_7
optional bool use_chronological_backtracking = 330 [default = false];- Returns:
- This builder for chaining.
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hasMaxBackjumpLevels
public boolean hasMaxBackjumpLevels()If chronological backtracking is enabled, this is the maximum number of levels we will backjump over, otherwise we will backtrack.
optional int32 max_backjump_levels = 331 [default = 50];- Specified by:
hasMaxBackjumpLevelsin interfaceSatParametersOrBuilder- Returns:
- Whether the maxBackjumpLevels field is set.
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getMaxBackjumpLevels
public int getMaxBackjumpLevels()If chronological backtracking is enabled, this is the maximum number of levels we will backjump over, otherwise we will backtrack.
optional int32 max_backjump_levels = 331 [default = 50];- Specified by:
getMaxBackjumpLevelsin interfaceSatParametersOrBuilder- Returns:
- The maxBackjumpLevels.
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setMaxBackjumpLevels
If chronological backtracking is enabled, this is the maximum number of levels we will backjump over, otherwise we will backtrack.
optional int32 max_backjump_levels = 331 [default = 50];- Parameters:
value- The maxBackjumpLevels to set.- Returns:
- This builder for chaining.
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clearMaxBackjumpLevels
If chronological backtracking is enabled, this is the maximum number of levels we will backjump over, otherwise we will backtrack.
optional int32 max_backjump_levels = 331 [default = 50];- Returns:
- This builder for chaining.
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hasChronologicalBacktrackMinConflicts
public boolean hasChronologicalBacktrackMinConflicts()If chronological backtracking is enabled, this is the minimum number of conflicts before we will consider backjumping.
optional int32 chronological_backtrack_min_conflicts = 332 [default = 1000];- Specified by:
hasChronologicalBacktrackMinConflictsin interfaceSatParametersOrBuilder- Returns:
- Whether the chronologicalBacktrackMinConflicts field is set.
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getChronologicalBacktrackMinConflicts
public int getChronologicalBacktrackMinConflicts()If chronological backtracking is enabled, this is the minimum number of conflicts before we will consider backjumping.
optional int32 chronological_backtrack_min_conflicts = 332 [default = 1000];- Specified by:
getChronologicalBacktrackMinConflictsin interfaceSatParametersOrBuilder- Returns:
- The chronologicalBacktrackMinConflicts.
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setChronologicalBacktrackMinConflicts
If chronological backtracking is enabled, this is the minimum number of conflicts before we will consider backjumping.
optional int32 chronological_backtrack_min_conflicts = 332 [default = 1000];- Parameters:
value- The chronologicalBacktrackMinConflicts to set.- Returns:
- This builder for chaining.
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clearChronologicalBacktrackMinConflicts
If chronological backtracking is enabled, this is the minimum number of conflicts before we will consider backjumping.
optional int32 chronological_backtrack_min_conflicts = 332 [default = 1000];- Returns:
- This builder for chaining.
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hasClauseCleanupPeriod
public boolean hasClauseCleanupPeriod()Trigger a cleanup when this number of "deletable" clauses is learned.
optional int32 clause_cleanup_period = 11 [default = 10000];- Specified by:
hasClauseCleanupPeriodin interfaceSatParametersOrBuilder- Returns:
- Whether the clauseCleanupPeriod field is set.
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getClauseCleanupPeriod
public int getClauseCleanupPeriod()Trigger a cleanup when this number of "deletable" clauses is learned.
optional int32 clause_cleanup_period = 11 [default = 10000];- Specified by:
getClauseCleanupPeriodin interfaceSatParametersOrBuilder- Returns:
- The clauseCleanupPeriod.
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setClauseCleanupPeriod
Trigger a cleanup when this number of "deletable" clauses is learned.
optional int32 clause_cleanup_period = 11 [default = 10000];- Parameters:
value- The clauseCleanupPeriod to set.- Returns:
- This builder for chaining.
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clearClauseCleanupPeriod
Trigger a cleanup when this number of "deletable" clauses is learned.
optional int32 clause_cleanup_period = 11 [default = 10000];- Returns:
- This builder for chaining.
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hasClauseCleanupPeriodIncrement
public boolean hasClauseCleanupPeriodIncrement()Increase clause_cleanup_period by this amount after each cleanup.
optional int32 clause_cleanup_period_increment = 337 [default = 0];- Specified by:
hasClauseCleanupPeriodIncrementin interfaceSatParametersOrBuilder- Returns:
- Whether the clauseCleanupPeriodIncrement field is set.
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getClauseCleanupPeriodIncrement
public int getClauseCleanupPeriodIncrement()Increase clause_cleanup_period by this amount after each cleanup.
optional int32 clause_cleanup_period_increment = 337 [default = 0];- Specified by:
getClauseCleanupPeriodIncrementin interfaceSatParametersOrBuilder- Returns:
- The clauseCleanupPeriodIncrement.
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setClauseCleanupPeriodIncrement
Increase clause_cleanup_period by this amount after each cleanup.
optional int32 clause_cleanup_period_increment = 337 [default = 0];- Parameters:
value- The clauseCleanupPeriodIncrement to set.- Returns:
- This builder for chaining.
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clearClauseCleanupPeriodIncrement
Increase clause_cleanup_period by this amount after each cleanup.
optional int32 clause_cleanup_period_increment = 337 [default = 0];- Returns:
- This builder for chaining.
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hasClauseCleanupTarget
public boolean hasClauseCleanupTarget()During a cleanup, we will always keep that number of "deletable" clauses. Note that this doesn't include the "protected" clauses.
optional int32 clause_cleanup_target = 13 [default = 0];- Specified by:
hasClauseCleanupTargetin interfaceSatParametersOrBuilder- Returns:
- Whether the clauseCleanupTarget field is set.
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getClauseCleanupTarget
public int getClauseCleanupTarget()During a cleanup, we will always keep that number of "deletable" clauses. Note that this doesn't include the "protected" clauses.
optional int32 clause_cleanup_target = 13 [default = 0];- Specified by:
getClauseCleanupTargetin interfaceSatParametersOrBuilder- Returns:
- The clauseCleanupTarget.
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setClauseCleanupTarget
During a cleanup, we will always keep that number of "deletable" clauses. Note that this doesn't include the "protected" clauses.
optional int32 clause_cleanup_target = 13 [default = 0];- Parameters:
value- The clauseCleanupTarget to set.- Returns:
- This builder for chaining.
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clearClauseCleanupTarget
During a cleanup, we will always keep that number of "deletable" clauses. Note that this doesn't include the "protected" clauses.
optional int32 clause_cleanup_target = 13 [default = 0];- Returns:
- This builder for chaining.
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hasClauseCleanupRatio
public boolean hasClauseCleanupRatio()During a cleanup, if clause_cleanup_target is 0, we will delete the clause_cleanup_ratio of "deletable" clauses instead of aiming for a fixed target of clauses to keep.
optional double clause_cleanup_ratio = 190 [default = 0.5];- Specified by:
hasClauseCleanupRatioin interfaceSatParametersOrBuilder- Returns:
- Whether the clauseCleanupRatio field is set.
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getClauseCleanupRatio
public double getClauseCleanupRatio()During a cleanup, if clause_cleanup_target is 0, we will delete the clause_cleanup_ratio of "deletable" clauses instead of aiming for a fixed target of clauses to keep.
optional double clause_cleanup_ratio = 190 [default = 0.5];- Specified by:
getClauseCleanupRatioin interfaceSatParametersOrBuilder- Returns:
- The clauseCleanupRatio.
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setClauseCleanupRatio
During a cleanup, if clause_cleanup_target is 0, we will delete the clause_cleanup_ratio of "deletable" clauses instead of aiming for a fixed target of clauses to keep.
optional double clause_cleanup_ratio = 190 [default = 0.5];- Parameters:
value- The clauseCleanupRatio to set.- Returns:
- This builder for chaining.
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clearClauseCleanupRatio
During a cleanup, if clause_cleanup_target is 0, we will delete the clause_cleanup_ratio of "deletable" clauses instead of aiming for a fixed target of clauses to keep.
optional double clause_cleanup_ratio = 190 [default = 0.5];- Returns:
- This builder for chaining.
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hasClauseCleanupLbdBound
public boolean hasClauseCleanupLbdBound()All the clauses with a LBD (literal blocks distance) lower or equal to this parameters will always be kept. Note that the LBD of a clause that just propagated is 1 + number of different decision levels of its literals. So that the "classic" LBD of a learned conflict is the same as its LBD when we backjump and then propagate it.
optional int32 clause_cleanup_lbd_bound = 59 [default = 5];- Specified by:
hasClauseCleanupLbdBoundin interfaceSatParametersOrBuilder- Returns:
- Whether the clauseCleanupLbdBound field is set.
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getClauseCleanupLbdBound
public int getClauseCleanupLbdBound()All the clauses with a LBD (literal blocks distance) lower or equal to this parameters will always be kept. Note that the LBD of a clause that just propagated is 1 + number of different decision levels of its literals. So that the "classic" LBD of a learned conflict is the same as its LBD when we backjump and then propagate it.
optional int32 clause_cleanup_lbd_bound = 59 [default = 5];- Specified by:
getClauseCleanupLbdBoundin interfaceSatParametersOrBuilder- Returns:
- The clauseCleanupLbdBound.
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setClauseCleanupLbdBound
All the clauses with a LBD (literal blocks distance) lower or equal to this parameters will always be kept. Note that the LBD of a clause that just propagated is 1 + number of different decision levels of its literals. So that the "classic" LBD of a learned conflict is the same as its LBD when we backjump and then propagate it.
optional int32 clause_cleanup_lbd_bound = 59 [default = 5];- Parameters:
value- The clauseCleanupLbdBound to set.- Returns:
- This builder for chaining.
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clearClauseCleanupLbdBound
All the clauses with a LBD (literal blocks distance) lower or equal to this parameters will always be kept. Note that the LBD of a clause that just propagated is 1 + number of different decision levels of its literals. So that the "classic" LBD of a learned conflict is the same as its LBD when we backjump and then propagate it.
optional int32 clause_cleanup_lbd_bound = 59 [default = 5];- Returns:
- This builder for chaining.
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hasClauseCleanupLbdTier1
public boolean hasClauseCleanupLbdTier1()All the clause with a LBD lower or equal to this will be kept except if its activity hasn't been bumped in the last 32 cleanup phase. Note that this has no effect if it is <= clause_cleanup_lbd_bound.
optional int32 clause_cleanup_lbd_tier1 = 349 [default = 0];- Specified by:
hasClauseCleanupLbdTier1in interfaceSatParametersOrBuilder- Returns:
- Whether the clauseCleanupLbdTier1 field is set.
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getClauseCleanupLbdTier1
public int getClauseCleanupLbdTier1()All the clause with a LBD lower or equal to this will be kept except if its activity hasn't been bumped in the last 32 cleanup phase. Note that this has no effect if it is <= clause_cleanup_lbd_bound.
optional int32 clause_cleanup_lbd_tier1 = 349 [default = 0];- Specified by:
getClauseCleanupLbdTier1in interfaceSatParametersOrBuilder- Returns:
- The clauseCleanupLbdTier1.
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setClauseCleanupLbdTier1
All the clause with a LBD lower or equal to this will be kept except if its activity hasn't been bumped in the last 32 cleanup phase. Note that this has no effect if it is <= clause_cleanup_lbd_bound.
optional int32 clause_cleanup_lbd_tier1 = 349 [default = 0];- Parameters:
value- The clauseCleanupLbdTier1 to set.- Returns:
- This builder for chaining.
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clearClauseCleanupLbdTier1
All the clause with a LBD lower or equal to this will be kept except if its activity hasn't been bumped in the last 32 cleanup phase. Note that this has no effect if it is <= clause_cleanup_lbd_bound.
optional int32 clause_cleanup_lbd_tier1 = 349 [default = 0];- Returns:
- This builder for chaining.
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hasClauseCleanupLbdTier2
public boolean hasClauseCleanupLbdTier2()All the clause with a LBD lower or equal to this will be kept except if its activity hasn't been bumped since the previous cleanup phase. Note that this has no effect if it is <= clause_cleanup_lbd_bound or <= clause_cleanup_lbd_tier1.
optional int32 clause_cleanup_lbd_tier2 = 350 [default = 0];- Specified by:
hasClauseCleanupLbdTier2in interfaceSatParametersOrBuilder- Returns:
- Whether the clauseCleanupLbdTier2 field is set.
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getClauseCleanupLbdTier2
public int getClauseCleanupLbdTier2()All the clause with a LBD lower or equal to this will be kept except if its activity hasn't been bumped since the previous cleanup phase. Note that this has no effect if it is <= clause_cleanup_lbd_bound or <= clause_cleanup_lbd_tier1.
optional int32 clause_cleanup_lbd_tier2 = 350 [default = 0];- Specified by:
getClauseCleanupLbdTier2in interfaceSatParametersOrBuilder- Returns:
- The clauseCleanupLbdTier2.
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setClauseCleanupLbdTier2
All the clause with a LBD lower or equal to this will be kept except if its activity hasn't been bumped since the previous cleanup phase. Note that this has no effect if it is <= clause_cleanup_lbd_bound or <= clause_cleanup_lbd_tier1.
optional int32 clause_cleanup_lbd_tier2 = 350 [default = 0];- Parameters:
value- The clauseCleanupLbdTier2 to set.- Returns:
- This builder for chaining.
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clearClauseCleanupLbdTier2
All the clause with a LBD lower or equal to this will be kept except if its activity hasn't been bumped since the previous cleanup phase. Note that this has no effect if it is <= clause_cleanup_lbd_bound or <= clause_cleanup_lbd_tier1.
optional int32 clause_cleanup_lbd_tier2 = 350 [default = 0];- Returns:
- This builder for chaining.
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hasClauseCleanupOrdering
public boolean hasClauseCleanupOrdering()optional .operations_research.sat.SatParameters.ClauseOrdering clause_cleanup_ordering = 60 [default = CLAUSE_ACTIVITY];- Specified by:
hasClauseCleanupOrderingin interfaceSatParametersOrBuilder- Returns:
- Whether the clauseCleanupOrdering field is set.
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getClauseCleanupOrdering
optional .operations_research.sat.SatParameters.ClauseOrdering clause_cleanup_ordering = 60 [default = CLAUSE_ACTIVITY];- Specified by:
getClauseCleanupOrderingin interfaceSatParametersOrBuilder- Returns:
- The clauseCleanupOrdering.
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setClauseCleanupOrdering
optional .operations_research.sat.SatParameters.ClauseOrdering clause_cleanup_ordering = 60 [default = CLAUSE_ACTIVITY];- Parameters:
value- The clauseCleanupOrdering to set.- Returns:
- This builder for chaining.
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clearClauseCleanupOrdering
optional .operations_research.sat.SatParameters.ClauseOrdering clause_cleanup_ordering = 60 [default = CLAUSE_ACTIVITY];- Returns:
- This builder for chaining.
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hasPbCleanupIncrement
public boolean hasPbCleanupIncrement()Same as for the clauses, but for the learned pseudo-Boolean constraints.
optional int32 pb_cleanup_increment = 46 [default = 200];- Specified by:
hasPbCleanupIncrementin interfaceSatParametersOrBuilder- Returns:
- Whether the pbCleanupIncrement field is set.
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getPbCleanupIncrement
public int getPbCleanupIncrement()Same as for the clauses, but for the learned pseudo-Boolean constraints.
optional int32 pb_cleanup_increment = 46 [default = 200];- Specified by:
getPbCleanupIncrementin interfaceSatParametersOrBuilder- Returns:
- The pbCleanupIncrement.
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setPbCleanupIncrement
Same as for the clauses, but for the learned pseudo-Boolean constraints.
optional int32 pb_cleanup_increment = 46 [default = 200];- Parameters:
value- The pbCleanupIncrement to set.- Returns:
- This builder for chaining.
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clearPbCleanupIncrement
Same as for the clauses, but for the learned pseudo-Boolean constraints.
optional int32 pb_cleanup_increment = 46 [default = 200];- Returns:
- This builder for chaining.
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hasPbCleanupRatio
public boolean hasPbCleanupRatio()optional double pb_cleanup_ratio = 47 [default = 0.5];- Specified by:
hasPbCleanupRatioin interfaceSatParametersOrBuilder- Returns:
- Whether the pbCleanupRatio field is set.
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getPbCleanupRatio
public double getPbCleanupRatio()optional double pb_cleanup_ratio = 47 [default = 0.5];- Specified by:
getPbCleanupRatioin interfaceSatParametersOrBuilder- Returns:
- The pbCleanupRatio.
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setPbCleanupRatio
optional double pb_cleanup_ratio = 47 [default = 0.5];- Parameters:
value- The pbCleanupRatio to set.- Returns:
- This builder for chaining.
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clearPbCleanupRatio
optional double pb_cleanup_ratio = 47 [default = 0.5];- Returns:
- This builder for chaining.
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hasVariableActivityDecay
public boolean hasVariableActivityDecay()Each time a conflict is found, the activities of some variables are increased by one. Then, the activity of all variables are multiplied by variable_activity_decay. To implement this efficiently, the activity of all the variables is not decayed at each conflict. Instead, the activity increment is multiplied by 1 / decay. When an activity reach max_variable_activity_value, all the activity are multiplied by 1 / max_variable_activity_value.
optional double variable_activity_decay = 15 [default = 0.8];- Specified by:
hasVariableActivityDecayin interfaceSatParametersOrBuilder- Returns:
- Whether the variableActivityDecay field is set.
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getVariableActivityDecay
public double getVariableActivityDecay()Each time a conflict is found, the activities of some variables are increased by one. Then, the activity of all variables are multiplied by variable_activity_decay. To implement this efficiently, the activity of all the variables is not decayed at each conflict. Instead, the activity increment is multiplied by 1 / decay. When an activity reach max_variable_activity_value, all the activity are multiplied by 1 / max_variable_activity_value.
optional double variable_activity_decay = 15 [default = 0.8];- Specified by:
getVariableActivityDecayin interfaceSatParametersOrBuilder- Returns:
- The variableActivityDecay.
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setVariableActivityDecay
Each time a conflict is found, the activities of some variables are increased by one. Then, the activity of all variables are multiplied by variable_activity_decay. To implement this efficiently, the activity of all the variables is not decayed at each conflict. Instead, the activity increment is multiplied by 1 / decay. When an activity reach max_variable_activity_value, all the activity are multiplied by 1 / max_variable_activity_value.
optional double variable_activity_decay = 15 [default = 0.8];- Parameters:
value- The variableActivityDecay to set.- Returns:
- This builder for chaining.
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clearVariableActivityDecay
Each time a conflict is found, the activities of some variables are increased by one. Then, the activity of all variables are multiplied by variable_activity_decay. To implement this efficiently, the activity of all the variables is not decayed at each conflict. Instead, the activity increment is multiplied by 1 / decay. When an activity reach max_variable_activity_value, all the activity are multiplied by 1 / max_variable_activity_value.
optional double variable_activity_decay = 15 [default = 0.8];- Returns:
- This builder for chaining.
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hasMaxVariableActivityValue
public boolean hasMaxVariableActivityValue()optional double max_variable_activity_value = 16 [default = 1e+100];- Specified by:
hasMaxVariableActivityValuein interfaceSatParametersOrBuilder- Returns:
- Whether the maxVariableActivityValue field is set.
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getMaxVariableActivityValue
public double getMaxVariableActivityValue()optional double max_variable_activity_value = 16 [default = 1e+100];- Specified by:
getMaxVariableActivityValuein interfaceSatParametersOrBuilder- Returns:
- The maxVariableActivityValue.
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setMaxVariableActivityValue
optional double max_variable_activity_value = 16 [default = 1e+100];- Parameters:
value- The maxVariableActivityValue to set.- Returns:
- This builder for chaining.
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clearMaxVariableActivityValue
optional double max_variable_activity_value = 16 [default = 1e+100];- Returns:
- This builder for chaining.
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hasGlucoseMaxDecay
public boolean hasGlucoseMaxDecay()The activity starts at 0.8 and increment by 0.01 every 5000 conflicts until 0.95. This "hack" seems to work well and comes from: Glucose 2.3 in the SAT 2013 Competition - SAT Competition 2013 http://edacc4.informatik.uni-ulm.de/SC13/solver-description-download/136
optional double glucose_max_decay = 22 [default = 0.95];- Specified by:
hasGlucoseMaxDecayin interfaceSatParametersOrBuilder- Returns:
- Whether the glucoseMaxDecay field is set.
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getGlucoseMaxDecay
public double getGlucoseMaxDecay()The activity starts at 0.8 and increment by 0.01 every 5000 conflicts until 0.95. This "hack" seems to work well and comes from: Glucose 2.3 in the SAT 2013 Competition - SAT Competition 2013 http://edacc4.informatik.uni-ulm.de/SC13/solver-description-download/136
optional double glucose_max_decay = 22 [default = 0.95];- Specified by:
getGlucoseMaxDecayin interfaceSatParametersOrBuilder- Returns:
- The glucoseMaxDecay.
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setGlucoseMaxDecay
The activity starts at 0.8 and increment by 0.01 every 5000 conflicts until 0.95. This "hack" seems to work well and comes from: Glucose 2.3 in the SAT 2013 Competition - SAT Competition 2013 http://edacc4.informatik.uni-ulm.de/SC13/solver-description-download/136
optional double glucose_max_decay = 22 [default = 0.95];- Parameters:
value- The glucoseMaxDecay to set.- Returns:
- This builder for chaining.
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clearGlucoseMaxDecay
The activity starts at 0.8 and increment by 0.01 every 5000 conflicts until 0.95. This "hack" seems to work well and comes from: Glucose 2.3 in the SAT 2013 Competition - SAT Competition 2013 http://edacc4.informatik.uni-ulm.de/SC13/solver-description-download/136
optional double glucose_max_decay = 22 [default = 0.95];- Returns:
- This builder for chaining.
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hasGlucoseDecayIncrement
public boolean hasGlucoseDecayIncrement()optional double glucose_decay_increment = 23 [default = 0.01];- Specified by:
hasGlucoseDecayIncrementin interfaceSatParametersOrBuilder- Returns:
- Whether the glucoseDecayIncrement field is set.
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getGlucoseDecayIncrement
public double getGlucoseDecayIncrement()optional double glucose_decay_increment = 23 [default = 0.01];- Specified by:
getGlucoseDecayIncrementin interfaceSatParametersOrBuilder- Returns:
- The glucoseDecayIncrement.
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setGlucoseDecayIncrement
optional double glucose_decay_increment = 23 [default = 0.01];- Parameters:
value- The glucoseDecayIncrement to set.- Returns:
- This builder for chaining.
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clearGlucoseDecayIncrement
optional double glucose_decay_increment = 23 [default = 0.01];- Returns:
- This builder for chaining.
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hasGlucoseDecayIncrementPeriod
public boolean hasGlucoseDecayIncrementPeriod()optional int32 glucose_decay_increment_period = 24 [default = 5000];- Specified by:
hasGlucoseDecayIncrementPeriodin interfaceSatParametersOrBuilder- Returns:
- Whether the glucoseDecayIncrementPeriod field is set.
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getGlucoseDecayIncrementPeriod
public int getGlucoseDecayIncrementPeriod()optional int32 glucose_decay_increment_period = 24 [default = 5000];- Specified by:
getGlucoseDecayIncrementPeriodin interfaceSatParametersOrBuilder- Returns:
- The glucoseDecayIncrementPeriod.
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setGlucoseDecayIncrementPeriod
optional int32 glucose_decay_increment_period = 24 [default = 5000];- Parameters:
value- The glucoseDecayIncrementPeriod to set.- Returns:
- This builder for chaining.
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clearGlucoseDecayIncrementPeriod
optional int32 glucose_decay_increment_period = 24 [default = 5000];- Returns:
- This builder for chaining.
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hasClauseActivityDecay
public boolean hasClauseActivityDecay()Clause activity parameters (same effect as the one on the variables).
optional double clause_activity_decay = 17 [default = 0.999];- Specified by:
hasClauseActivityDecayin interfaceSatParametersOrBuilder- Returns:
- Whether the clauseActivityDecay field is set.
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getClauseActivityDecay
public double getClauseActivityDecay()Clause activity parameters (same effect as the one on the variables).
optional double clause_activity_decay = 17 [default = 0.999];- Specified by:
getClauseActivityDecayin interfaceSatParametersOrBuilder- Returns:
- The clauseActivityDecay.
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setClauseActivityDecay
Clause activity parameters (same effect as the one on the variables).
optional double clause_activity_decay = 17 [default = 0.999];- Parameters:
value- The clauseActivityDecay to set.- Returns:
- This builder for chaining.
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clearClauseActivityDecay
Clause activity parameters (same effect as the one on the variables).
optional double clause_activity_decay = 17 [default = 0.999];- Returns:
- This builder for chaining.
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hasMaxClauseActivityValue
public boolean hasMaxClauseActivityValue()optional double max_clause_activity_value = 18 [default = 1e+20];- Specified by:
hasMaxClauseActivityValuein interfaceSatParametersOrBuilder- Returns:
- Whether the maxClauseActivityValue field is set.
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getMaxClauseActivityValue
public double getMaxClauseActivityValue()optional double max_clause_activity_value = 18 [default = 1e+20];- Specified by:
getMaxClauseActivityValuein interfaceSatParametersOrBuilder- Returns:
- The maxClauseActivityValue.
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setMaxClauseActivityValue
optional double max_clause_activity_value = 18 [default = 1e+20];- Parameters:
value- The maxClauseActivityValue to set.- Returns:
- This builder for chaining.
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clearMaxClauseActivityValue
optional double max_clause_activity_value = 18 [default = 1e+20];- Returns:
- This builder for chaining.
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getRestartAlgorithmsList
The restart strategies will change each time the strategy_counter is increased. The current strategy will simply be the one at index strategy_counter modulo the number of strategy. Note that if this list includes a NO_RESTART, nothing will change when it is reached because the strategy_counter will only increment after a restart. The idea of switching of search strategy tailored for SAT/UNSAT comes from Chanseok Oh with his COMiniSatPS solver, see http://cs.nyu.edu/~chanseok/. But more generally, it seems REALLY beneficial to try different strategy.
repeated .operations_research.sat.SatParameters.RestartAlgorithm restart_algorithms = 61;- Specified by:
getRestartAlgorithmsListin interfaceSatParametersOrBuilder- Returns:
- A list containing the restartAlgorithms.
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getRestartAlgorithmsCount
public int getRestartAlgorithmsCount()The restart strategies will change each time the strategy_counter is increased. The current strategy will simply be the one at index strategy_counter modulo the number of strategy. Note that if this list includes a NO_RESTART, nothing will change when it is reached because the strategy_counter will only increment after a restart. The idea of switching of search strategy tailored for SAT/UNSAT comes from Chanseok Oh with his COMiniSatPS solver, see http://cs.nyu.edu/~chanseok/. But more generally, it seems REALLY beneficial to try different strategy.
repeated .operations_research.sat.SatParameters.RestartAlgorithm restart_algorithms = 61;- Specified by:
getRestartAlgorithmsCountin interfaceSatParametersOrBuilder- Returns:
- The count of restartAlgorithms.
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getRestartAlgorithms
The restart strategies will change each time the strategy_counter is increased. The current strategy will simply be the one at index strategy_counter modulo the number of strategy. Note that if this list includes a NO_RESTART, nothing will change when it is reached because the strategy_counter will only increment after a restart. The idea of switching of search strategy tailored for SAT/UNSAT comes from Chanseok Oh with his COMiniSatPS solver, see http://cs.nyu.edu/~chanseok/. But more generally, it seems REALLY beneficial to try different strategy.
repeated .operations_research.sat.SatParameters.RestartAlgorithm restart_algorithms = 61;- Specified by:
getRestartAlgorithmsin interfaceSatParametersOrBuilder- Parameters:
index- The index of the element to return.- Returns:
- The restartAlgorithms at the given index.
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setRestartAlgorithms
The restart strategies will change each time the strategy_counter is increased. The current strategy will simply be the one at index strategy_counter modulo the number of strategy. Note that if this list includes a NO_RESTART, nothing will change when it is reached because the strategy_counter will only increment after a restart. The idea of switching of search strategy tailored for SAT/UNSAT comes from Chanseok Oh with his COMiniSatPS solver, see http://cs.nyu.edu/~chanseok/. But more generally, it seems REALLY beneficial to try different strategy.
repeated .operations_research.sat.SatParameters.RestartAlgorithm restart_algorithms = 61;- Parameters:
index- The index to set the value at.value- The restartAlgorithms to set.- Returns:
- This builder for chaining.
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addRestartAlgorithms
The restart strategies will change each time the strategy_counter is increased. The current strategy will simply be the one at index strategy_counter modulo the number of strategy. Note that if this list includes a NO_RESTART, nothing will change when it is reached because the strategy_counter will only increment after a restart. The idea of switching of search strategy tailored for SAT/UNSAT comes from Chanseok Oh with his COMiniSatPS solver, see http://cs.nyu.edu/~chanseok/. But more generally, it seems REALLY beneficial to try different strategy.
repeated .operations_research.sat.SatParameters.RestartAlgorithm restart_algorithms = 61;- Parameters:
value- The restartAlgorithms to add.- Returns:
- This builder for chaining.
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addAllRestartAlgorithms
public SatParameters.Builder addAllRestartAlgorithms(Iterable<? extends SatParameters.RestartAlgorithm> values) The restart strategies will change each time the strategy_counter is increased. The current strategy will simply be the one at index strategy_counter modulo the number of strategy. Note that if this list includes a NO_RESTART, nothing will change when it is reached because the strategy_counter will only increment after a restart. The idea of switching of search strategy tailored for SAT/UNSAT comes from Chanseok Oh with his COMiniSatPS solver, see http://cs.nyu.edu/~chanseok/. But more generally, it seems REALLY beneficial to try different strategy.
repeated .operations_research.sat.SatParameters.RestartAlgorithm restart_algorithms = 61;- Parameters:
values- The restartAlgorithms to add.- Returns:
- This builder for chaining.
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clearRestartAlgorithms
The restart strategies will change each time the strategy_counter is increased. The current strategy will simply be the one at index strategy_counter modulo the number of strategy. Note that if this list includes a NO_RESTART, nothing will change when it is reached because the strategy_counter will only increment after a restart. The idea of switching of search strategy tailored for SAT/UNSAT comes from Chanseok Oh with his COMiniSatPS solver, see http://cs.nyu.edu/~chanseok/. But more generally, it seems REALLY beneficial to try different strategy.
repeated .operations_research.sat.SatParameters.RestartAlgorithm restart_algorithms = 61;- Returns:
- This builder for chaining.
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hasDefaultRestartAlgorithms
public boolean hasDefaultRestartAlgorithms()optional string default_restart_algorithms = 70 [default = "LUBY_RESTART,LBD_MOVING_AVERAGE_RESTART,DL_MOVING_AVERAGE_RESTART"];- Specified by:
hasDefaultRestartAlgorithmsin interfaceSatParametersOrBuilder- Returns:
- Whether the defaultRestartAlgorithms field is set.
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getDefaultRestartAlgorithms
optional string default_restart_algorithms = 70 [default = "LUBY_RESTART,LBD_MOVING_AVERAGE_RESTART,DL_MOVING_AVERAGE_RESTART"];- Specified by:
getDefaultRestartAlgorithmsin interfaceSatParametersOrBuilder- Returns:
- The defaultRestartAlgorithms.
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getDefaultRestartAlgorithmsBytes
public com.google.protobuf.ByteString getDefaultRestartAlgorithmsBytes()optional string default_restart_algorithms = 70 [default = "LUBY_RESTART,LBD_MOVING_AVERAGE_RESTART,DL_MOVING_AVERAGE_RESTART"];- Specified by:
getDefaultRestartAlgorithmsBytesin interfaceSatParametersOrBuilder- Returns:
- The bytes for defaultRestartAlgorithms.
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setDefaultRestartAlgorithms
optional string default_restart_algorithms = 70 [default = "LUBY_RESTART,LBD_MOVING_AVERAGE_RESTART,DL_MOVING_AVERAGE_RESTART"];- Parameters:
value- The defaultRestartAlgorithms to set.- Returns:
- This builder for chaining.
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clearDefaultRestartAlgorithms
optional string default_restart_algorithms = 70 [default = "LUBY_RESTART,LBD_MOVING_AVERAGE_RESTART,DL_MOVING_AVERAGE_RESTART"];- Returns:
- This builder for chaining.
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setDefaultRestartAlgorithmsBytes
optional string default_restart_algorithms = 70 [default = "LUBY_RESTART,LBD_MOVING_AVERAGE_RESTART,DL_MOVING_AVERAGE_RESTART"];- Parameters:
value- The bytes for defaultRestartAlgorithms to set.- Returns:
- This builder for chaining.
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hasRestartPeriod
public boolean hasRestartPeriod()Restart period for the FIXED_RESTART strategy. This is also the multiplier used by the LUBY_RESTART strategy.
optional int32 restart_period = 30 [default = 50];- Specified by:
hasRestartPeriodin interfaceSatParametersOrBuilder- Returns:
- Whether the restartPeriod field is set.
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getRestartPeriod
public int getRestartPeriod()Restart period for the FIXED_RESTART strategy. This is also the multiplier used by the LUBY_RESTART strategy.
optional int32 restart_period = 30 [default = 50];- Specified by:
getRestartPeriodin interfaceSatParametersOrBuilder- Returns:
- The restartPeriod.
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setRestartPeriod
Restart period for the FIXED_RESTART strategy. This is also the multiplier used by the LUBY_RESTART strategy.
optional int32 restart_period = 30 [default = 50];- Parameters:
value- The restartPeriod to set.- Returns:
- This builder for chaining.
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clearRestartPeriod
Restart period for the FIXED_RESTART strategy. This is also the multiplier used by the LUBY_RESTART strategy.
optional int32 restart_period = 30 [default = 50];- Returns:
- This builder for chaining.
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hasRestartRunningWindowSize
public boolean hasRestartRunningWindowSize()Size of the window for the moving average restarts.
optional int32 restart_running_window_size = 62 [default = 50];- Specified by:
hasRestartRunningWindowSizein interfaceSatParametersOrBuilder- Returns:
- Whether the restartRunningWindowSize field is set.
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getRestartRunningWindowSize
public int getRestartRunningWindowSize()Size of the window for the moving average restarts.
optional int32 restart_running_window_size = 62 [default = 50];- Specified by:
getRestartRunningWindowSizein interfaceSatParametersOrBuilder- Returns:
- The restartRunningWindowSize.
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setRestartRunningWindowSize
Size of the window for the moving average restarts.
optional int32 restart_running_window_size = 62 [default = 50];- Parameters:
value- The restartRunningWindowSize to set.- Returns:
- This builder for chaining.
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clearRestartRunningWindowSize
Size of the window for the moving average restarts.
optional int32 restart_running_window_size = 62 [default = 50];- Returns:
- This builder for chaining.
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hasRestartDlAverageRatio
public boolean hasRestartDlAverageRatio()In the moving average restart algorithms, a restart is triggered if the window average times this ratio is greater that the global average.
optional double restart_dl_average_ratio = 63 [default = 1];- Specified by:
hasRestartDlAverageRatioin interfaceSatParametersOrBuilder- Returns:
- Whether the restartDlAverageRatio field is set.
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getRestartDlAverageRatio
public double getRestartDlAverageRatio()In the moving average restart algorithms, a restart is triggered if the window average times this ratio is greater that the global average.
optional double restart_dl_average_ratio = 63 [default = 1];- Specified by:
getRestartDlAverageRatioin interfaceSatParametersOrBuilder- Returns:
- The restartDlAverageRatio.
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setRestartDlAverageRatio
In the moving average restart algorithms, a restart is triggered if the window average times this ratio is greater that the global average.
optional double restart_dl_average_ratio = 63 [default = 1];- Parameters:
value- The restartDlAverageRatio to set.- Returns:
- This builder for chaining.
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clearRestartDlAverageRatio
In the moving average restart algorithms, a restart is triggered if the window average times this ratio is greater that the global average.
optional double restart_dl_average_ratio = 63 [default = 1];- Returns:
- This builder for chaining.
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hasRestartLbdAverageRatio
public boolean hasRestartLbdAverageRatio()optional double restart_lbd_average_ratio = 71 [default = 1];- Specified by:
hasRestartLbdAverageRatioin interfaceSatParametersOrBuilder- Returns:
- Whether the restartLbdAverageRatio field is set.
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getRestartLbdAverageRatio
public double getRestartLbdAverageRatio()optional double restart_lbd_average_ratio = 71 [default = 1];- Specified by:
getRestartLbdAverageRatioin interfaceSatParametersOrBuilder- Returns:
- The restartLbdAverageRatio.
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setRestartLbdAverageRatio
optional double restart_lbd_average_ratio = 71 [default = 1];- Parameters:
value- The restartLbdAverageRatio to set.- Returns:
- This builder for chaining.
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clearRestartLbdAverageRatio
optional double restart_lbd_average_ratio = 71 [default = 1];- Returns:
- This builder for chaining.
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hasUseBlockingRestart
public boolean hasUseBlockingRestart()Block a moving restart algorithm if the trail size of the current conflict is greater than the multiplier times the moving average of the trail size at the previous conflicts.
optional bool use_blocking_restart = 64 [default = false];- Specified by:
hasUseBlockingRestartin interfaceSatParametersOrBuilder- Returns:
- Whether the useBlockingRestart field is set.
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getUseBlockingRestart
public boolean getUseBlockingRestart()Block a moving restart algorithm if the trail size of the current conflict is greater than the multiplier times the moving average of the trail size at the previous conflicts.
optional bool use_blocking_restart = 64 [default = false];- Specified by:
getUseBlockingRestartin interfaceSatParametersOrBuilder- Returns:
- The useBlockingRestart.
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setUseBlockingRestart
Block a moving restart algorithm if the trail size of the current conflict is greater than the multiplier times the moving average of the trail size at the previous conflicts.
optional bool use_blocking_restart = 64 [default = false];- Parameters:
value- The useBlockingRestart to set.- Returns:
- This builder for chaining.
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clearUseBlockingRestart
Block a moving restart algorithm if the trail size of the current conflict is greater than the multiplier times the moving average of the trail size at the previous conflicts.
optional bool use_blocking_restart = 64 [default = false];- Returns:
- This builder for chaining.
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hasBlockingRestartWindowSize
public boolean hasBlockingRestartWindowSize()optional int32 blocking_restart_window_size = 65 [default = 5000];- Specified by:
hasBlockingRestartWindowSizein interfaceSatParametersOrBuilder- Returns:
- Whether the blockingRestartWindowSize field is set.
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getBlockingRestartWindowSize
public int getBlockingRestartWindowSize()optional int32 blocking_restart_window_size = 65 [default = 5000];- Specified by:
getBlockingRestartWindowSizein interfaceSatParametersOrBuilder- Returns:
- The blockingRestartWindowSize.
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setBlockingRestartWindowSize
optional int32 blocking_restart_window_size = 65 [default = 5000];- Parameters:
value- The blockingRestartWindowSize to set.- Returns:
- This builder for chaining.
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clearBlockingRestartWindowSize
optional int32 blocking_restart_window_size = 65 [default = 5000];- Returns:
- This builder for chaining.
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hasBlockingRestartMultiplier
public boolean hasBlockingRestartMultiplier()optional double blocking_restart_multiplier = 66 [default = 1.4];- Specified by:
hasBlockingRestartMultiplierin interfaceSatParametersOrBuilder- Returns:
- Whether the blockingRestartMultiplier field is set.
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getBlockingRestartMultiplier
public double getBlockingRestartMultiplier()optional double blocking_restart_multiplier = 66 [default = 1.4];- Specified by:
getBlockingRestartMultiplierin interfaceSatParametersOrBuilder- Returns:
- The blockingRestartMultiplier.
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setBlockingRestartMultiplier
optional double blocking_restart_multiplier = 66 [default = 1.4];- Parameters:
value- The blockingRestartMultiplier to set.- Returns:
- This builder for chaining.
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clearBlockingRestartMultiplier
optional double blocking_restart_multiplier = 66 [default = 1.4];- Returns:
- This builder for chaining.
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hasNumConflictsBeforeStrategyChanges
public boolean hasNumConflictsBeforeStrategyChanges()After each restart, if the number of conflict since the last strategy change is greater that this, then we increment a "strategy_counter" that can be use to change the search strategy used by the following restarts.
optional int32 num_conflicts_before_strategy_changes = 68 [default = 0];- Specified by:
hasNumConflictsBeforeStrategyChangesin interfaceSatParametersOrBuilder- Returns:
- Whether the numConflictsBeforeStrategyChanges field is set.
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getNumConflictsBeforeStrategyChanges
public int getNumConflictsBeforeStrategyChanges()After each restart, if the number of conflict since the last strategy change is greater that this, then we increment a "strategy_counter" that can be use to change the search strategy used by the following restarts.
optional int32 num_conflicts_before_strategy_changes = 68 [default = 0];- Specified by:
getNumConflictsBeforeStrategyChangesin interfaceSatParametersOrBuilder- Returns:
- The numConflictsBeforeStrategyChanges.
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setNumConflictsBeforeStrategyChanges
After each restart, if the number of conflict since the last strategy change is greater that this, then we increment a "strategy_counter" that can be use to change the search strategy used by the following restarts.
optional int32 num_conflicts_before_strategy_changes = 68 [default = 0];- Parameters:
value- The numConflictsBeforeStrategyChanges to set.- Returns:
- This builder for chaining.
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clearNumConflictsBeforeStrategyChanges
After each restart, if the number of conflict since the last strategy change is greater that this, then we increment a "strategy_counter" that can be use to change the search strategy used by the following restarts.
optional int32 num_conflicts_before_strategy_changes = 68 [default = 0];- Returns:
- This builder for chaining.
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hasStrategyChangeIncreaseRatio
public boolean hasStrategyChangeIncreaseRatio()The parameter num_conflicts_before_strategy_changes is increased by that much after each strategy change.
optional double strategy_change_increase_ratio = 69 [default = 0];- Specified by:
hasStrategyChangeIncreaseRatioin interfaceSatParametersOrBuilder- Returns:
- Whether the strategyChangeIncreaseRatio field is set.
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getStrategyChangeIncreaseRatio
public double getStrategyChangeIncreaseRatio()The parameter num_conflicts_before_strategy_changes is increased by that much after each strategy change.
optional double strategy_change_increase_ratio = 69 [default = 0];- Specified by:
getStrategyChangeIncreaseRatioin interfaceSatParametersOrBuilder- Returns:
- The strategyChangeIncreaseRatio.
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setStrategyChangeIncreaseRatio
The parameter num_conflicts_before_strategy_changes is increased by that much after each strategy change.
optional double strategy_change_increase_ratio = 69 [default = 0];- Parameters:
value- The strategyChangeIncreaseRatio to set.- Returns:
- This builder for chaining.
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clearStrategyChangeIncreaseRatio
The parameter num_conflicts_before_strategy_changes is increased by that much after each strategy change.
optional double strategy_change_increase_ratio = 69 [default = 0];- Returns:
- This builder for chaining.
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hasMaxTimeInSeconds
public boolean hasMaxTimeInSeconds()Maximum time allowed in seconds to solve a problem. The counter will starts at the beginning of the Solve() call.
optional double max_time_in_seconds = 36 [default = inf];- Specified by:
hasMaxTimeInSecondsin interfaceSatParametersOrBuilder- Returns:
- Whether the maxTimeInSeconds field is set.
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getMaxTimeInSeconds
public double getMaxTimeInSeconds()Maximum time allowed in seconds to solve a problem. The counter will starts at the beginning of the Solve() call.
optional double max_time_in_seconds = 36 [default = inf];- Specified by:
getMaxTimeInSecondsin interfaceSatParametersOrBuilder- Returns:
- The maxTimeInSeconds.
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setMaxTimeInSeconds
Maximum time allowed in seconds to solve a problem. The counter will starts at the beginning of the Solve() call.
optional double max_time_in_seconds = 36 [default = inf];- Parameters:
value- The maxTimeInSeconds to set.- Returns:
- This builder for chaining.
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clearMaxTimeInSeconds
Maximum time allowed in seconds to solve a problem. The counter will starts at the beginning of the Solve() call.
optional double max_time_in_seconds = 36 [default = inf];- Returns:
- This builder for chaining.
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hasMaxDeterministicTime
public boolean hasMaxDeterministicTime()Maximum time allowed in deterministic time to solve a problem. The deterministic time should be correlated with the real time used by the solver, the time unit being as close as possible to a second.
optional double max_deterministic_time = 67 [default = inf];- Specified by:
hasMaxDeterministicTimein interfaceSatParametersOrBuilder- Returns:
- Whether the maxDeterministicTime field is set.
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getMaxDeterministicTime
public double getMaxDeterministicTime()Maximum time allowed in deterministic time to solve a problem. The deterministic time should be correlated with the real time used by the solver, the time unit being as close as possible to a second.
optional double max_deterministic_time = 67 [default = inf];- Specified by:
getMaxDeterministicTimein interfaceSatParametersOrBuilder- Returns:
- The maxDeterministicTime.
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setMaxDeterministicTime
Maximum time allowed in deterministic time to solve a problem. The deterministic time should be correlated with the real time used by the solver, the time unit being as close as possible to a second.
optional double max_deterministic_time = 67 [default = inf];- Parameters:
value- The maxDeterministicTime to set.- Returns:
- This builder for chaining.
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clearMaxDeterministicTime
Maximum time allowed in deterministic time to solve a problem. The deterministic time should be correlated with the real time used by the solver, the time unit being as close as possible to a second.
optional double max_deterministic_time = 67 [default = inf];- Returns:
- This builder for chaining.
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hasMaxNumDeterministicBatches
public boolean hasMaxNumDeterministicBatches()Stops after that number of batches has been scheduled. This only make sense when interleave_search is true.
optional int32 max_num_deterministic_batches = 291 [default = 0];- Specified by:
hasMaxNumDeterministicBatchesin interfaceSatParametersOrBuilder- Returns:
- Whether the maxNumDeterministicBatches field is set.
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getMaxNumDeterministicBatches
public int getMaxNumDeterministicBatches()Stops after that number of batches has been scheduled. This only make sense when interleave_search is true.
optional int32 max_num_deterministic_batches = 291 [default = 0];- Specified by:
getMaxNumDeterministicBatchesin interfaceSatParametersOrBuilder- Returns:
- The maxNumDeterministicBatches.
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setMaxNumDeterministicBatches
Stops after that number of batches has been scheduled. This only make sense when interleave_search is true.
optional int32 max_num_deterministic_batches = 291 [default = 0];- Parameters:
value- The maxNumDeterministicBatches to set.- Returns:
- This builder for chaining.
-
clearMaxNumDeterministicBatches
Stops after that number of batches has been scheduled. This only make sense when interleave_search is true.
optional int32 max_num_deterministic_batches = 291 [default = 0];- Returns:
- This builder for chaining.
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hasMaxNumberOfConflicts
public boolean hasMaxNumberOfConflicts()Maximum number of conflicts allowed to solve a problem. TODO(user): Maybe change the way the conflict limit is enforced? currently it is enforced on each independent internal SAT solve, rather than on the overall number of conflicts across all solves. So in the context of an optimization problem, this is not really usable directly by a client.
optional int64 max_number_of_conflicts = 37 [default = 9223372036854775807];- Specified by:
hasMaxNumberOfConflictsin interfaceSatParametersOrBuilder- Returns:
- Whether the maxNumberOfConflicts field is set.
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getMaxNumberOfConflicts
public long getMaxNumberOfConflicts()Maximum number of conflicts allowed to solve a problem. TODO(user): Maybe change the way the conflict limit is enforced? currently it is enforced on each independent internal SAT solve, rather than on the overall number of conflicts across all solves. So in the context of an optimization problem, this is not really usable directly by a client.
optional int64 max_number_of_conflicts = 37 [default = 9223372036854775807];- Specified by:
getMaxNumberOfConflictsin interfaceSatParametersOrBuilder- Returns:
- The maxNumberOfConflicts.
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setMaxNumberOfConflicts
Maximum number of conflicts allowed to solve a problem. TODO(user): Maybe change the way the conflict limit is enforced? currently it is enforced on each independent internal SAT solve, rather than on the overall number of conflicts across all solves. So in the context of an optimization problem, this is not really usable directly by a client.
optional int64 max_number_of_conflicts = 37 [default = 9223372036854775807];- Parameters:
value- The maxNumberOfConflicts to set.- Returns:
- This builder for chaining.
-
clearMaxNumberOfConflicts
Maximum number of conflicts allowed to solve a problem. TODO(user): Maybe change the way the conflict limit is enforced? currently it is enforced on each independent internal SAT solve, rather than on the overall number of conflicts across all solves. So in the context of an optimization problem, this is not really usable directly by a client.
optional int64 max_number_of_conflicts = 37 [default = 9223372036854775807];- Returns:
- This builder for chaining.
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hasMaxMemoryInMb
public boolean hasMaxMemoryInMb()Maximum memory allowed for the whole thread containing the solver. The solver will abort as soon as it detects that this limit is crossed. As a result, this limit is approximative, but usually the solver will not go too much over. TODO(user): This is only used by the pure SAT solver, generalize to CP-SAT.
optional int64 max_memory_in_mb = 40 [default = 10000];- Specified by:
hasMaxMemoryInMbin interfaceSatParametersOrBuilder- Returns:
- Whether the maxMemoryInMb field is set.
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getMaxMemoryInMb
public long getMaxMemoryInMb()Maximum memory allowed for the whole thread containing the solver. The solver will abort as soon as it detects that this limit is crossed. As a result, this limit is approximative, but usually the solver will not go too much over. TODO(user): This is only used by the pure SAT solver, generalize to CP-SAT.
optional int64 max_memory_in_mb = 40 [default = 10000];- Specified by:
getMaxMemoryInMbin interfaceSatParametersOrBuilder- Returns:
- The maxMemoryInMb.
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setMaxMemoryInMb
Maximum memory allowed for the whole thread containing the solver. The solver will abort as soon as it detects that this limit is crossed. As a result, this limit is approximative, but usually the solver will not go too much over. TODO(user): This is only used by the pure SAT solver, generalize to CP-SAT.
optional int64 max_memory_in_mb = 40 [default = 10000];- Parameters:
value- The maxMemoryInMb to set.- Returns:
- This builder for chaining.
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clearMaxMemoryInMb
Maximum memory allowed for the whole thread containing the solver. The solver will abort as soon as it detects that this limit is crossed. As a result, this limit is approximative, but usually the solver will not go too much over. TODO(user): This is only used by the pure SAT solver, generalize to CP-SAT.
optional int64 max_memory_in_mb = 40 [default = 10000];- Returns:
- This builder for chaining.
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hasAbsoluteGapLimit
public boolean hasAbsoluteGapLimit()Stop the search when the gap between the best feasible objective (O) and our best objective bound (B) is smaller than a limit. The exact definition is: - Absolute: abs(O - B) - Relative: abs(O - B) / max(1, abs(O)). Important: The relative gap depends on the objective offset! If you artificially shift the objective, you will get widely different value of the relative gap. Note that if the gap is reached, the search status will be OPTIMAL. But one can check the best objective bound to see the actual gap. If the objective is integer, then any absolute gap < 1 will lead to a true optimal. If the objective is floating point, a gap of zero make little sense so is is why we use a non-zero default value. At the end of the search, we will display a warning if OPTIMAL is reported yet the gap is greater than this absolute gap.
optional double absolute_gap_limit = 159 [default = 0.0001];- Specified by:
hasAbsoluteGapLimitin interfaceSatParametersOrBuilder- Returns:
- Whether the absoluteGapLimit field is set.
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getAbsoluteGapLimit
public double getAbsoluteGapLimit()Stop the search when the gap between the best feasible objective (O) and our best objective bound (B) is smaller than a limit. The exact definition is: - Absolute: abs(O - B) - Relative: abs(O - B) / max(1, abs(O)). Important: The relative gap depends on the objective offset! If you artificially shift the objective, you will get widely different value of the relative gap. Note that if the gap is reached, the search status will be OPTIMAL. But one can check the best objective bound to see the actual gap. If the objective is integer, then any absolute gap < 1 will lead to a true optimal. If the objective is floating point, a gap of zero make little sense so is is why we use a non-zero default value. At the end of the search, we will display a warning if OPTIMAL is reported yet the gap is greater than this absolute gap.
optional double absolute_gap_limit = 159 [default = 0.0001];- Specified by:
getAbsoluteGapLimitin interfaceSatParametersOrBuilder- Returns:
- The absoluteGapLimit.
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setAbsoluteGapLimit
Stop the search when the gap between the best feasible objective (O) and our best objective bound (B) is smaller than a limit. The exact definition is: - Absolute: abs(O - B) - Relative: abs(O - B) / max(1, abs(O)). Important: The relative gap depends on the objective offset! If you artificially shift the objective, you will get widely different value of the relative gap. Note that if the gap is reached, the search status will be OPTIMAL. But one can check the best objective bound to see the actual gap. If the objective is integer, then any absolute gap < 1 will lead to a true optimal. If the objective is floating point, a gap of zero make little sense so is is why we use a non-zero default value. At the end of the search, we will display a warning if OPTIMAL is reported yet the gap is greater than this absolute gap.
optional double absolute_gap_limit = 159 [default = 0.0001];- Parameters:
value- The absoluteGapLimit to set.- Returns:
- This builder for chaining.
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clearAbsoluteGapLimit
Stop the search when the gap between the best feasible objective (O) and our best objective bound (B) is smaller than a limit. The exact definition is: - Absolute: abs(O - B) - Relative: abs(O - B) / max(1, abs(O)). Important: The relative gap depends on the objective offset! If you artificially shift the objective, you will get widely different value of the relative gap. Note that if the gap is reached, the search status will be OPTIMAL. But one can check the best objective bound to see the actual gap. If the objective is integer, then any absolute gap < 1 will lead to a true optimal. If the objective is floating point, a gap of zero make little sense so is is why we use a non-zero default value. At the end of the search, we will display a warning if OPTIMAL is reported yet the gap is greater than this absolute gap.
optional double absolute_gap_limit = 159 [default = 0.0001];- Returns:
- This builder for chaining.
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hasRelativeGapLimit
public boolean hasRelativeGapLimit()optional double relative_gap_limit = 160 [default = 0];- Specified by:
hasRelativeGapLimitin interfaceSatParametersOrBuilder- Returns:
- Whether the relativeGapLimit field is set.
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getRelativeGapLimit
public double getRelativeGapLimit()optional double relative_gap_limit = 160 [default = 0];- Specified by:
getRelativeGapLimitin interfaceSatParametersOrBuilder- Returns:
- The relativeGapLimit.
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setRelativeGapLimit
optional double relative_gap_limit = 160 [default = 0];- Parameters:
value- The relativeGapLimit to set.- Returns:
- This builder for chaining.
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clearRelativeGapLimit
optional double relative_gap_limit = 160 [default = 0];- Returns:
- This builder for chaining.
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hasRandomSeed
public boolean hasRandomSeed()At the beginning of each solve, the random number generator used in some part of the solver is reinitialized to this seed. If you change the random seed, the solver may make different choices during the solving process. For some problems, the running time may vary a lot depending on small change in the solving algorithm. Running the solver with different seeds enables to have more robust benchmarks when evaluating new features.
optional int32 random_seed = 31 [default = 1];- Specified by:
hasRandomSeedin interfaceSatParametersOrBuilder- Returns:
- Whether the randomSeed field is set.
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getRandomSeed
public int getRandomSeed()At the beginning of each solve, the random number generator used in some part of the solver is reinitialized to this seed. If you change the random seed, the solver may make different choices during the solving process. For some problems, the running time may vary a lot depending on small change in the solving algorithm. Running the solver with different seeds enables to have more robust benchmarks when evaluating new features.
optional int32 random_seed = 31 [default = 1];- Specified by:
getRandomSeedin interfaceSatParametersOrBuilder- Returns:
- The randomSeed.
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setRandomSeed
At the beginning of each solve, the random number generator used in some part of the solver is reinitialized to this seed. If you change the random seed, the solver may make different choices during the solving process. For some problems, the running time may vary a lot depending on small change in the solving algorithm. Running the solver with different seeds enables to have more robust benchmarks when evaluating new features.
optional int32 random_seed = 31 [default = 1];- Parameters:
value- The randomSeed to set.- Returns:
- This builder for chaining.
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clearRandomSeed
At the beginning of each solve, the random number generator used in some part of the solver is reinitialized to this seed. If you change the random seed, the solver may make different choices during the solving process. For some problems, the running time may vary a lot depending on small change in the solving algorithm. Running the solver with different seeds enables to have more robust benchmarks when evaluating new features.
optional int32 random_seed = 31 [default = 1];- Returns:
- This builder for chaining.
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hasPermuteVariableRandomly
public boolean hasPermuteVariableRandomly()This is mainly here to test the solver variability. Note that in tests, if not explicitly set to false, all 3 options will be set to true so that clients do not rely on the solver returning a specific solution if they are many equivalent optimal solutions.
optional bool permute_variable_randomly = 178 [default = false];- Specified by:
hasPermuteVariableRandomlyin interfaceSatParametersOrBuilder- Returns:
- Whether the permuteVariableRandomly field is set.
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getPermuteVariableRandomly
public boolean getPermuteVariableRandomly()This is mainly here to test the solver variability. Note that in tests, if not explicitly set to false, all 3 options will be set to true so that clients do not rely on the solver returning a specific solution if they are many equivalent optimal solutions.
optional bool permute_variable_randomly = 178 [default = false];- Specified by:
getPermuteVariableRandomlyin interfaceSatParametersOrBuilder- Returns:
- The permuteVariableRandomly.
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setPermuteVariableRandomly
This is mainly here to test the solver variability. Note that in tests, if not explicitly set to false, all 3 options will be set to true so that clients do not rely on the solver returning a specific solution if they are many equivalent optimal solutions.
optional bool permute_variable_randomly = 178 [default = false];- Parameters:
value- The permuteVariableRandomly to set.- Returns:
- This builder for chaining.
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clearPermuteVariableRandomly
This is mainly here to test the solver variability. Note that in tests, if not explicitly set to false, all 3 options will be set to true so that clients do not rely on the solver returning a specific solution if they are many equivalent optimal solutions.
optional bool permute_variable_randomly = 178 [default = false];- Returns:
- This builder for chaining.
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hasPermutePresolveConstraintOrder
public boolean hasPermutePresolveConstraintOrder()optional bool permute_presolve_constraint_order = 179 [default = false];- Specified by:
hasPermutePresolveConstraintOrderin interfaceSatParametersOrBuilder- Returns:
- Whether the permutePresolveConstraintOrder field is set.
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getPermutePresolveConstraintOrder
public boolean getPermutePresolveConstraintOrder()optional bool permute_presolve_constraint_order = 179 [default = false];- Specified by:
getPermutePresolveConstraintOrderin interfaceSatParametersOrBuilder- Returns:
- The permutePresolveConstraintOrder.
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setPermutePresolveConstraintOrder
optional bool permute_presolve_constraint_order = 179 [default = false];- Parameters:
value- The permutePresolveConstraintOrder to set.- Returns:
- This builder for chaining.
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clearPermutePresolveConstraintOrder
optional bool permute_presolve_constraint_order = 179 [default = false];- Returns:
- This builder for chaining.
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hasUseAbslRandom
public boolean hasUseAbslRandom()optional bool use_absl_random = 180 [default = false];- Specified by:
hasUseAbslRandomin interfaceSatParametersOrBuilder- Returns:
- Whether the useAbslRandom field is set.
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getUseAbslRandom
public boolean getUseAbslRandom()optional bool use_absl_random = 180 [default = false];- Specified by:
getUseAbslRandomin interfaceSatParametersOrBuilder- Returns:
- The useAbslRandom.
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setUseAbslRandom
optional bool use_absl_random = 180 [default = false];- Parameters:
value- The useAbslRandom to set.- Returns:
- This builder for chaining.
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clearUseAbslRandom
optional bool use_absl_random = 180 [default = false];- Returns:
- This builder for chaining.
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hasLogSearchProgress
public boolean hasLogSearchProgress()Whether the solver should log the search progress. This is the maing logging parameter and if this is false, none of the logging (callbacks, log_to_stdout, log_to_response, ...) will do anything.
optional bool log_search_progress = 41 [default = false];- Specified by:
hasLogSearchProgressin interfaceSatParametersOrBuilder- Returns:
- Whether the logSearchProgress field is set.
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getLogSearchProgress
public boolean getLogSearchProgress()Whether the solver should log the search progress. This is the maing logging parameter and if this is false, none of the logging (callbacks, log_to_stdout, log_to_response, ...) will do anything.
optional bool log_search_progress = 41 [default = false];- Specified by:
getLogSearchProgressin interfaceSatParametersOrBuilder- Returns:
- The logSearchProgress.
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setLogSearchProgress
Whether the solver should log the search progress. This is the maing logging parameter and if this is false, none of the logging (callbacks, log_to_stdout, log_to_response, ...) will do anything.
optional bool log_search_progress = 41 [default = false];- Parameters:
value- The logSearchProgress to set.- Returns:
- This builder for chaining.
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clearLogSearchProgress
Whether the solver should log the search progress. This is the maing logging parameter and if this is false, none of the logging (callbacks, log_to_stdout, log_to_response, ...) will do anything.
optional bool log_search_progress = 41 [default = false];- Returns:
- This builder for chaining.
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hasLogSubsolverStatistics
public boolean hasLogSubsolverStatistics()Whether the solver should display per sub-solver search statistics. This is only useful is log_search_progress is set to true, and if the number of search workers is > 1. Note that in all case we display a bit of stats with one line per subsolver.
optional bool log_subsolver_statistics = 189 [default = false];- Specified by:
hasLogSubsolverStatisticsin interfaceSatParametersOrBuilder- Returns:
- Whether the logSubsolverStatistics field is set.
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getLogSubsolverStatistics
public boolean getLogSubsolverStatistics()Whether the solver should display per sub-solver search statistics. This is only useful is log_search_progress is set to true, and if the number of search workers is > 1. Note that in all case we display a bit of stats with one line per subsolver.
optional bool log_subsolver_statistics = 189 [default = false];- Specified by:
getLogSubsolverStatisticsin interfaceSatParametersOrBuilder- Returns:
- The logSubsolverStatistics.
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setLogSubsolverStatistics
Whether the solver should display per sub-solver search statistics. This is only useful is log_search_progress is set to true, and if the number of search workers is > 1. Note that in all case we display a bit of stats with one line per subsolver.
optional bool log_subsolver_statistics = 189 [default = false];- Parameters:
value- The logSubsolverStatistics to set.- Returns:
- This builder for chaining.
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clearLogSubsolverStatistics
Whether the solver should display per sub-solver search statistics. This is only useful is log_search_progress is set to true, and if the number of search workers is > 1. Note that in all case we display a bit of stats with one line per subsolver.
optional bool log_subsolver_statistics = 189 [default = false];- Returns:
- This builder for chaining.
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hasLogPrefix
public boolean hasLogPrefix()Add a prefix to all logs.
optional string log_prefix = 185 [default = ""];- Specified by:
hasLogPrefixin interfaceSatParametersOrBuilder- Returns:
- Whether the logPrefix field is set.
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getLogPrefix
Add a prefix to all logs.
optional string log_prefix = 185 [default = ""];- Specified by:
getLogPrefixin interfaceSatParametersOrBuilder- Returns:
- The logPrefix.
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getLogPrefixBytes
public com.google.protobuf.ByteString getLogPrefixBytes()Add a prefix to all logs.
optional string log_prefix = 185 [default = ""];- Specified by:
getLogPrefixBytesin interfaceSatParametersOrBuilder- Returns:
- The bytes for logPrefix.
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setLogPrefix
Add a prefix to all logs.
optional string log_prefix = 185 [default = ""];- Parameters:
value- The logPrefix to set.- Returns:
- This builder for chaining.
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clearLogPrefix
Add a prefix to all logs.
optional string log_prefix = 185 [default = ""];- Returns:
- This builder for chaining.
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setLogPrefixBytes
Add a prefix to all logs.
optional string log_prefix = 185 [default = ""];- Parameters:
value- The bytes for logPrefix to set.- Returns:
- This builder for chaining.
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hasLogToStdout
public boolean hasLogToStdout()Log to stdout.
optional bool log_to_stdout = 186 [default = true];- Specified by:
hasLogToStdoutin interfaceSatParametersOrBuilder- Returns:
- Whether the logToStdout field is set.
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getLogToStdout
public boolean getLogToStdout()Log to stdout.
optional bool log_to_stdout = 186 [default = true];- Specified by:
getLogToStdoutin interfaceSatParametersOrBuilder- Returns:
- The logToStdout.
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setLogToStdout
Log to stdout.
optional bool log_to_stdout = 186 [default = true];- Parameters:
value- The logToStdout to set.- Returns:
- This builder for chaining.
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clearLogToStdout
Log to stdout.
optional bool log_to_stdout = 186 [default = true];- Returns:
- This builder for chaining.
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hasLogToResponse
public boolean hasLogToResponse()Log to response proto.
optional bool log_to_response = 187 [default = false];- Specified by:
hasLogToResponsein interfaceSatParametersOrBuilder- Returns:
- Whether the logToResponse field is set.
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getLogToResponse
public boolean getLogToResponse()Log to response proto.
optional bool log_to_response = 187 [default = false];- Specified by:
getLogToResponsein interfaceSatParametersOrBuilder- Returns:
- The logToResponse.
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setLogToResponse
Log to response proto.
optional bool log_to_response = 187 [default = false];- Parameters:
value- The logToResponse to set.- Returns:
- This builder for chaining.
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clearLogToResponse
Log to response proto.
optional bool log_to_response = 187 [default = false];- Returns:
- This builder for chaining.
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hasUsePbResolution
public boolean hasUsePbResolution()Experimental. This is an old experiment, it might cause crashes in multi-thread and you should double check the solver result. It can still be used if you only care about feasible solutions (these are checked) and it gives good result on your problem. We might revive it at some point. Whether to use pseudo-Boolean resolution to analyze a conflict. Note that this option only make sense if your problem is modelized using pseudo-Boolean constraints. If you only have clauses, this shouldn't change anything (except slow the solver down).
optional bool use_pb_resolution = 43 [default = false];- Specified by:
hasUsePbResolutionin interfaceSatParametersOrBuilder- Returns:
- Whether the usePbResolution field is set.
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getUsePbResolution
public boolean getUsePbResolution()Experimental. This is an old experiment, it might cause crashes in multi-thread and you should double check the solver result. It can still be used if you only care about feasible solutions (these are checked) and it gives good result on your problem. We might revive it at some point. Whether to use pseudo-Boolean resolution to analyze a conflict. Note that this option only make sense if your problem is modelized using pseudo-Boolean constraints. If you only have clauses, this shouldn't change anything (except slow the solver down).
optional bool use_pb_resolution = 43 [default = false];- Specified by:
getUsePbResolutionin interfaceSatParametersOrBuilder- Returns:
- The usePbResolution.
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setUsePbResolution
Experimental. This is an old experiment, it might cause crashes in multi-thread and you should double check the solver result. It can still be used if you only care about feasible solutions (these are checked) and it gives good result on your problem. We might revive it at some point. Whether to use pseudo-Boolean resolution to analyze a conflict. Note that this option only make sense if your problem is modelized using pseudo-Boolean constraints. If you only have clauses, this shouldn't change anything (except slow the solver down).
optional bool use_pb_resolution = 43 [default = false];- Parameters:
value- The usePbResolution to set.- Returns:
- This builder for chaining.
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clearUsePbResolution
Experimental. This is an old experiment, it might cause crashes in multi-thread and you should double check the solver result. It can still be used if you only care about feasible solutions (these are checked) and it gives good result on your problem. We might revive it at some point. Whether to use pseudo-Boolean resolution to analyze a conflict. Note that this option only make sense if your problem is modelized using pseudo-Boolean constraints. If you only have clauses, this shouldn't change anything (except slow the solver down).
optional bool use_pb_resolution = 43 [default = false];- Returns:
- This builder for chaining.
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hasMinimizeReductionDuringPbResolution
public boolean hasMinimizeReductionDuringPbResolution()A different algorithm during PB resolution. It minimizes the number of calls to ReduceCoefficients() which can be time consuming. However, the search space will be different and if the coefficients are large, this may lead to integer overflows that could otherwise be prevented.
optional bool minimize_reduction_during_pb_resolution = 48 [default = false];- Specified by:
hasMinimizeReductionDuringPbResolutionin interfaceSatParametersOrBuilder- Returns:
- Whether the minimizeReductionDuringPbResolution field is set.
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getMinimizeReductionDuringPbResolution
public boolean getMinimizeReductionDuringPbResolution()A different algorithm during PB resolution. It minimizes the number of calls to ReduceCoefficients() which can be time consuming. However, the search space will be different and if the coefficients are large, this may lead to integer overflows that could otherwise be prevented.
optional bool minimize_reduction_during_pb_resolution = 48 [default = false];- Specified by:
getMinimizeReductionDuringPbResolutionin interfaceSatParametersOrBuilder- Returns:
- The minimizeReductionDuringPbResolution.
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setMinimizeReductionDuringPbResolution
A different algorithm during PB resolution. It minimizes the number of calls to ReduceCoefficients() which can be time consuming. However, the search space will be different and if the coefficients are large, this may lead to integer overflows that could otherwise be prevented.
optional bool minimize_reduction_during_pb_resolution = 48 [default = false];- Parameters:
value- The minimizeReductionDuringPbResolution to set.- Returns:
- This builder for chaining.
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clearMinimizeReductionDuringPbResolution
A different algorithm during PB resolution. It minimizes the number of calls to ReduceCoefficients() which can be time consuming. However, the search space will be different and if the coefficients are large, this may lead to integer overflows that could otherwise be prevented.
optional bool minimize_reduction_during_pb_resolution = 48 [default = false];- Returns:
- This builder for chaining.
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hasCountAssumptionLevelsInLbd
public boolean hasCountAssumptionLevelsInLbd()Whether or not the assumption levels are taken into account during the LBD computation. According to the reference below, not counting them improves the solver in some situation. Note that this only impact solves under assumptions. Gilles Audemard, Jean-Marie Lagniez, Laurent Simon, "Improving Glucose for Incremental SAT Solving with Assumptions: Application to MUS Extraction" Theory and Applications of Satisfiability Testing - SAT 2013, Lecture Notes in Computer Science Volume 7962, 2013, pp 309-317.
optional bool count_assumption_levels_in_lbd = 49 [default = true];- Specified by:
hasCountAssumptionLevelsInLbdin interfaceSatParametersOrBuilder- Returns:
- Whether the countAssumptionLevelsInLbd field is set.
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getCountAssumptionLevelsInLbd
public boolean getCountAssumptionLevelsInLbd()Whether or not the assumption levels are taken into account during the LBD computation. According to the reference below, not counting them improves the solver in some situation. Note that this only impact solves under assumptions. Gilles Audemard, Jean-Marie Lagniez, Laurent Simon, "Improving Glucose for Incremental SAT Solving with Assumptions: Application to MUS Extraction" Theory and Applications of Satisfiability Testing - SAT 2013, Lecture Notes in Computer Science Volume 7962, 2013, pp 309-317.
optional bool count_assumption_levels_in_lbd = 49 [default = true];- Specified by:
getCountAssumptionLevelsInLbdin interfaceSatParametersOrBuilder- Returns:
- The countAssumptionLevelsInLbd.
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setCountAssumptionLevelsInLbd
Whether or not the assumption levels are taken into account during the LBD computation. According to the reference below, not counting them improves the solver in some situation. Note that this only impact solves under assumptions. Gilles Audemard, Jean-Marie Lagniez, Laurent Simon, "Improving Glucose for Incremental SAT Solving with Assumptions: Application to MUS Extraction" Theory and Applications of Satisfiability Testing - SAT 2013, Lecture Notes in Computer Science Volume 7962, 2013, pp 309-317.
optional bool count_assumption_levels_in_lbd = 49 [default = true];- Parameters:
value- The countAssumptionLevelsInLbd to set.- Returns:
- This builder for chaining.
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clearCountAssumptionLevelsInLbd
Whether or not the assumption levels are taken into account during the LBD computation. According to the reference below, not counting them improves the solver in some situation. Note that this only impact solves under assumptions. Gilles Audemard, Jean-Marie Lagniez, Laurent Simon, "Improving Glucose for Incremental SAT Solving with Assumptions: Application to MUS Extraction" Theory and Applications of Satisfiability Testing - SAT 2013, Lecture Notes in Computer Science Volume 7962, 2013, pp 309-317.
optional bool count_assumption_levels_in_lbd = 49 [default = true];- Returns:
- This builder for chaining.
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hasPresolveBveThreshold
public boolean hasPresolveBveThreshold()During presolve, only try to perform the bounded variable elimination (BVE) of a variable x if the number of occurrences of x times the number of occurrences of not(x) is not greater than this parameter.
optional int32 presolve_bve_threshold = 54 [default = 500];- Specified by:
hasPresolveBveThresholdin interfaceSatParametersOrBuilder- Returns:
- Whether the presolveBveThreshold field is set.
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getPresolveBveThreshold
public int getPresolveBveThreshold()During presolve, only try to perform the bounded variable elimination (BVE) of a variable x if the number of occurrences of x times the number of occurrences of not(x) is not greater than this parameter.
optional int32 presolve_bve_threshold = 54 [default = 500];- Specified by:
getPresolveBveThresholdin interfaceSatParametersOrBuilder- Returns:
- The presolveBveThreshold.
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setPresolveBveThreshold
During presolve, only try to perform the bounded variable elimination (BVE) of a variable x if the number of occurrences of x times the number of occurrences of not(x) is not greater than this parameter.
optional int32 presolve_bve_threshold = 54 [default = 500];- Parameters:
value- The presolveBveThreshold to set.- Returns:
- This builder for chaining.
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clearPresolveBveThreshold
During presolve, only try to perform the bounded variable elimination (BVE) of a variable x if the number of occurrences of x times the number of occurrences of not(x) is not greater than this parameter.
optional int32 presolve_bve_threshold = 54 [default = 500];- Returns:
- This builder for chaining.
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hasFilterSatPostsolveClauses
public boolean hasFilterSatPostsolveClauses()Internal parameter. During BVE, if we eliminate a variable x, by default we will push all clauses containing x and all clauses containing not(x) to the postsolve. However, it is possible to write the postsolve code so that only one such set is needed. The idea is that, if we push the set containing a literal l, is to set l to false except if it is needed to satisfy one of the clause in the set. This is always beneficial, but for historical reason, not all our postsolve algorithm support this.
optional bool filter_sat_postsolve_clauses = 324 [default = false];- Specified by:
hasFilterSatPostsolveClausesin interfaceSatParametersOrBuilder- Returns:
- Whether the filterSatPostsolveClauses field is set.
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getFilterSatPostsolveClauses
public boolean getFilterSatPostsolveClauses()Internal parameter. During BVE, if we eliminate a variable x, by default we will push all clauses containing x and all clauses containing not(x) to the postsolve. However, it is possible to write the postsolve code so that only one such set is needed. The idea is that, if we push the set containing a literal l, is to set l to false except if it is needed to satisfy one of the clause in the set. This is always beneficial, but for historical reason, not all our postsolve algorithm support this.
optional bool filter_sat_postsolve_clauses = 324 [default = false];- Specified by:
getFilterSatPostsolveClausesin interfaceSatParametersOrBuilder- Returns:
- The filterSatPostsolveClauses.
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setFilterSatPostsolveClauses
Internal parameter. During BVE, if we eliminate a variable x, by default we will push all clauses containing x and all clauses containing not(x) to the postsolve. However, it is possible to write the postsolve code so that only one such set is needed. The idea is that, if we push the set containing a literal l, is to set l to false except if it is needed to satisfy one of the clause in the set. This is always beneficial, but for historical reason, not all our postsolve algorithm support this.
optional bool filter_sat_postsolve_clauses = 324 [default = false];- Parameters:
value- The filterSatPostsolveClauses to set.- Returns:
- This builder for chaining.
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clearFilterSatPostsolveClauses
Internal parameter. During BVE, if we eliminate a variable x, by default we will push all clauses containing x and all clauses containing not(x) to the postsolve. However, it is possible to write the postsolve code so that only one such set is needed. The idea is that, if we push the set containing a literal l, is to set l to false except if it is needed to satisfy one of the clause in the set. This is always beneficial, but for historical reason, not all our postsolve algorithm support this.
optional bool filter_sat_postsolve_clauses = 324 [default = false];- Returns:
- This builder for chaining.
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hasPresolveBveClauseWeight
public boolean hasPresolveBveClauseWeight()During presolve, we apply BVE only if this weight times the number of clauses plus the number of clause literals is not increased.
optional int32 presolve_bve_clause_weight = 55 [default = 3];- Specified by:
hasPresolveBveClauseWeightin interfaceSatParametersOrBuilder- Returns:
- Whether the presolveBveClauseWeight field is set.
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getPresolveBveClauseWeight
public int getPresolveBveClauseWeight()During presolve, we apply BVE only if this weight times the number of clauses plus the number of clause literals is not increased.
optional int32 presolve_bve_clause_weight = 55 [default = 3];- Specified by:
getPresolveBveClauseWeightin interfaceSatParametersOrBuilder- Returns:
- The presolveBveClauseWeight.
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setPresolveBveClauseWeight
During presolve, we apply BVE only if this weight times the number of clauses plus the number of clause literals is not increased.
optional int32 presolve_bve_clause_weight = 55 [default = 3];- Parameters:
value- The presolveBveClauseWeight to set.- Returns:
- This builder for chaining.
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clearPresolveBveClauseWeight
During presolve, we apply BVE only if this weight times the number of clauses plus the number of clause literals is not increased.
optional int32 presolve_bve_clause_weight = 55 [default = 3];- Returns:
- This builder for chaining.
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hasProbingDeterministicTimeLimit
public boolean hasProbingDeterministicTimeLimit()The maximum "deterministic" time limit to spend in probing. A value of zero will disable the probing. TODO(user): Clean up. The first one is used in CP-SAT, the other in pure SAT presolve.
optional double probing_deterministic_time_limit = 226 [default = 1];- Specified by:
hasProbingDeterministicTimeLimitin interfaceSatParametersOrBuilder- Returns:
- Whether the probingDeterministicTimeLimit field is set.
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getProbingDeterministicTimeLimit
public double getProbingDeterministicTimeLimit()The maximum "deterministic" time limit to spend in probing. A value of zero will disable the probing. TODO(user): Clean up. The first one is used in CP-SAT, the other in pure SAT presolve.
optional double probing_deterministic_time_limit = 226 [default = 1];- Specified by:
getProbingDeterministicTimeLimitin interfaceSatParametersOrBuilder- Returns:
- The probingDeterministicTimeLimit.
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setProbingDeterministicTimeLimit
The maximum "deterministic" time limit to spend in probing. A value of zero will disable the probing. TODO(user): Clean up. The first one is used in CP-SAT, the other in pure SAT presolve.
optional double probing_deterministic_time_limit = 226 [default = 1];- Parameters:
value- The probingDeterministicTimeLimit to set.- Returns:
- This builder for chaining.
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clearProbingDeterministicTimeLimit
The maximum "deterministic" time limit to spend in probing. A value of zero will disable the probing. TODO(user): Clean up. The first one is used in CP-SAT, the other in pure SAT presolve.
optional double probing_deterministic_time_limit = 226 [default = 1];- Returns:
- This builder for chaining.
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hasPresolveProbingDeterministicTimeLimit
public boolean hasPresolveProbingDeterministicTimeLimit()optional double presolve_probing_deterministic_time_limit = 57 [default = 30];- Specified by:
hasPresolveProbingDeterministicTimeLimitin interfaceSatParametersOrBuilder- Returns:
- Whether the presolveProbingDeterministicTimeLimit field is set.
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getPresolveProbingDeterministicTimeLimit
public double getPresolveProbingDeterministicTimeLimit()optional double presolve_probing_deterministic_time_limit = 57 [default = 30];- Specified by:
getPresolveProbingDeterministicTimeLimitin interfaceSatParametersOrBuilder- Returns:
- The presolveProbingDeterministicTimeLimit.
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setPresolveProbingDeterministicTimeLimit
optional double presolve_probing_deterministic_time_limit = 57 [default = 30];- Parameters:
value- The presolveProbingDeterministicTimeLimit to set.- Returns:
- This builder for chaining.
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clearPresolveProbingDeterministicTimeLimit
optional double presolve_probing_deterministic_time_limit = 57 [default = 30];- Returns:
- This builder for chaining.
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hasPresolveBlockedClause
public boolean hasPresolveBlockedClause()Whether we use an heuristic to detect some basic case of blocked clause in the SAT presolve.
optional bool presolve_blocked_clause = 88 [default = true];- Specified by:
hasPresolveBlockedClausein interfaceSatParametersOrBuilder- Returns:
- Whether the presolveBlockedClause field is set.
-
getPresolveBlockedClause
public boolean getPresolveBlockedClause()Whether we use an heuristic to detect some basic case of blocked clause in the SAT presolve.
optional bool presolve_blocked_clause = 88 [default = true];- Specified by:
getPresolveBlockedClausein interfaceSatParametersOrBuilder- Returns:
- The presolveBlockedClause.
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setPresolveBlockedClause
Whether we use an heuristic to detect some basic case of blocked clause in the SAT presolve.
optional bool presolve_blocked_clause = 88 [default = true];- Parameters:
value- The presolveBlockedClause to set.- Returns:
- This builder for chaining.
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clearPresolveBlockedClause
Whether we use an heuristic to detect some basic case of blocked clause in the SAT presolve.
optional bool presolve_blocked_clause = 88 [default = true];- Returns:
- This builder for chaining.
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hasPresolveUseBva
public boolean hasPresolveUseBva()Whether or not we use Bounded Variable Addition (BVA) in the presolve.
optional bool presolve_use_bva = 72 [default = true];- Specified by:
hasPresolveUseBvain interfaceSatParametersOrBuilder- Returns:
- Whether the presolveUseBva field is set.
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getPresolveUseBva
public boolean getPresolveUseBva()Whether or not we use Bounded Variable Addition (BVA) in the presolve.
optional bool presolve_use_bva = 72 [default = true];- Specified by:
getPresolveUseBvain interfaceSatParametersOrBuilder- Returns:
- The presolveUseBva.
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setPresolveUseBva
Whether or not we use Bounded Variable Addition (BVA) in the presolve.
optional bool presolve_use_bva = 72 [default = true];- Parameters:
value- The presolveUseBva to set.- Returns:
- This builder for chaining.
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clearPresolveUseBva
Whether or not we use Bounded Variable Addition (BVA) in the presolve.
optional bool presolve_use_bva = 72 [default = true];- Returns:
- This builder for chaining.
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hasPresolveBvaThreshold
public boolean hasPresolveBvaThreshold()Apply Bounded Variable Addition (BVA) if the number of clauses is reduced by stricly more than this threshold. The algorithm described in the paper uses 0, but quick experiments showed that 1 is a good value. It may not be worth it to add a new variable just to remove one clause.
optional int32 presolve_bva_threshold = 73 [default = 1];- Specified by:
hasPresolveBvaThresholdin interfaceSatParametersOrBuilder- Returns:
- Whether the presolveBvaThreshold field is set.
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getPresolveBvaThreshold
public int getPresolveBvaThreshold()Apply Bounded Variable Addition (BVA) if the number of clauses is reduced by stricly more than this threshold. The algorithm described in the paper uses 0, but quick experiments showed that 1 is a good value. It may not be worth it to add a new variable just to remove one clause.
optional int32 presolve_bva_threshold = 73 [default = 1];- Specified by:
getPresolveBvaThresholdin interfaceSatParametersOrBuilder- Returns:
- The presolveBvaThreshold.
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setPresolveBvaThreshold
Apply Bounded Variable Addition (BVA) if the number of clauses is reduced by stricly more than this threshold. The algorithm described in the paper uses 0, but quick experiments showed that 1 is a good value. It may not be worth it to add a new variable just to remove one clause.
optional int32 presolve_bva_threshold = 73 [default = 1];- Parameters:
value- The presolveBvaThreshold to set.- Returns:
- This builder for chaining.
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clearPresolveBvaThreshold
Apply Bounded Variable Addition (BVA) if the number of clauses is reduced by stricly more than this threshold. The algorithm described in the paper uses 0, but quick experiments showed that 1 is a good value. It may not be worth it to add a new variable just to remove one clause.
optional int32 presolve_bva_threshold = 73 [default = 1];- Returns:
- This builder for chaining.
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hasMaxPresolveIterations
public boolean hasMaxPresolveIterations()In case of large reduction in a presolve iteration, we perform multiple presolve iterations. This parameter controls the maximum number of such presolve iterations.
optional int32 max_presolve_iterations = 138 [default = 3];- Specified by:
hasMaxPresolveIterationsin interfaceSatParametersOrBuilder- Returns:
- Whether the maxPresolveIterations field is set.
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getMaxPresolveIterations
public int getMaxPresolveIterations()In case of large reduction in a presolve iteration, we perform multiple presolve iterations. This parameter controls the maximum number of such presolve iterations.
optional int32 max_presolve_iterations = 138 [default = 3];- Specified by:
getMaxPresolveIterationsin interfaceSatParametersOrBuilder- Returns:
- The maxPresolveIterations.
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setMaxPresolveIterations
In case of large reduction in a presolve iteration, we perform multiple presolve iterations. This parameter controls the maximum number of such presolve iterations.
optional int32 max_presolve_iterations = 138 [default = 3];- Parameters:
value- The maxPresolveIterations to set.- Returns:
- This builder for chaining.
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clearMaxPresolveIterations
In case of large reduction in a presolve iteration, we perform multiple presolve iterations. This parameter controls the maximum number of such presolve iterations.
optional int32 max_presolve_iterations = 138 [default = 3];- Returns:
- This builder for chaining.
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hasCpModelPresolve
public boolean hasCpModelPresolve()Whether we presolve the cp_model before solving it.
optional bool cp_model_presolve = 86 [default = true];- Specified by:
hasCpModelPresolvein interfaceSatParametersOrBuilder- Returns:
- Whether the cpModelPresolve field is set.
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getCpModelPresolve
public boolean getCpModelPresolve()Whether we presolve the cp_model before solving it.
optional bool cp_model_presolve = 86 [default = true];- Specified by:
getCpModelPresolvein interfaceSatParametersOrBuilder- Returns:
- The cpModelPresolve.
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setCpModelPresolve
Whether we presolve the cp_model before solving it.
optional bool cp_model_presolve = 86 [default = true];- Parameters:
value- The cpModelPresolve to set.- Returns:
- This builder for chaining.
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clearCpModelPresolve
Whether we presolve the cp_model before solving it.
optional bool cp_model_presolve = 86 [default = true];- Returns:
- This builder for chaining.
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hasCpModelProbingLevel
public boolean hasCpModelProbingLevel()How much effort do we spend on probing. 0 disables it completely.
optional int32 cp_model_probing_level = 110 [default = 2];- Specified by:
hasCpModelProbingLevelin interfaceSatParametersOrBuilder- Returns:
- Whether the cpModelProbingLevel field is set.
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getCpModelProbingLevel
public int getCpModelProbingLevel()How much effort do we spend on probing. 0 disables it completely.
optional int32 cp_model_probing_level = 110 [default = 2];- Specified by:
getCpModelProbingLevelin interfaceSatParametersOrBuilder- Returns:
- The cpModelProbingLevel.
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setCpModelProbingLevel
How much effort do we spend on probing. 0 disables it completely.
optional int32 cp_model_probing_level = 110 [default = 2];- Parameters:
value- The cpModelProbingLevel to set.- Returns:
- This builder for chaining.
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clearCpModelProbingLevel
How much effort do we spend on probing. 0 disables it completely.
optional int32 cp_model_probing_level = 110 [default = 2];- Returns:
- This builder for chaining.
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hasCpModelUseSatPresolve
public boolean hasCpModelUseSatPresolve()Whether we also use the sat presolve when cp_model_presolve is true.
optional bool cp_model_use_sat_presolve = 93 [default = true];- Specified by:
hasCpModelUseSatPresolvein interfaceSatParametersOrBuilder- Returns:
- Whether the cpModelUseSatPresolve field is set.
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getCpModelUseSatPresolve
public boolean getCpModelUseSatPresolve()Whether we also use the sat presolve when cp_model_presolve is true.
optional bool cp_model_use_sat_presolve = 93 [default = true];- Specified by:
getCpModelUseSatPresolvein interfaceSatParametersOrBuilder- Returns:
- The cpModelUseSatPresolve.
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setCpModelUseSatPresolve
Whether we also use the sat presolve when cp_model_presolve is true.
optional bool cp_model_use_sat_presolve = 93 [default = true];- Parameters:
value- The cpModelUseSatPresolve to set.- Returns:
- This builder for chaining.
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clearCpModelUseSatPresolve
Whether we also use the sat presolve when cp_model_presolve is true.
optional bool cp_model_use_sat_presolve = 93 [default = true];- Returns:
- This builder for chaining.
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hasLoadAtMostOnesInSatPresolve
public boolean hasLoadAtMostOnesInSatPresolve()If we try to load at most ones and exactly ones constraints when running the pure SAT presolve. Or if we just ignore them. If one detects at_most_one via merge_at_most_one_work_limit or exactly one with find_clauses_that_are_exactly_one, it might be good to also set this to true.
optional bool load_at_most_ones_in_sat_presolve = 335 [default = false];- Specified by:
hasLoadAtMostOnesInSatPresolvein interfaceSatParametersOrBuilder- Returns:
- Whether the loadAtMostOnesInSatPresolve field is set.
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getLoadAtMostOnesInSatPresolve
public boolean getLoadAtMostOnesInSatPresolve()If we try to load at most ones and exactly ones constraints when running the pure SAT presolve. Or if we just ignore them. If one detects at_most_one via merge_at_most_one_work_limit or exactly one with find_clauses_that_are_exactly_one, it might be good to also set this to true.
optional bool load_at_most_ones_in_sat_presolve = 335 [default = false];- Specified by:
getLoadAtMostOnesInSatPresolvein interfaceSatParametersOrBuilder- Returns:
- The loadAtMostOnesInSatPresolve.
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setLoadAtMostOnesInSatPresolve
If we try to load at most ones and exactly ones constraints when running the pure SAT presolve. Or if we just ignore them. If one detects at_most_one via merge_at_most_one_work_limit or exactly one with find_clauses_that_are_exactly_one, it might be good to also set this to true.
optional bool load_at_most_ones_in_sat_presolve = 335 [default = false];- Parameters:
value- The loadAtMostOnesInSatPresolve to set.- Returns:
- This builder for chaining.
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clearLoadAtMostOnesInSatPresolve
If we try to load at most ones and exactly ones constraints when running the pure SAT presolve. Or if we just ignore them. If one detects at_most_one via merge_at_most_one_work_limit or exactly one with find_clauses_that_are_exactly_one, it might be good to also set this to true.
optional bool load_at_most_ones_in_sat_presolve = 335 [default = false];- Returns:
- This builder for chaining.
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hasRemoveFixedVariablesEarly
public boolean hasRemoveFixedVariablesEarly()If cp_model_presolve is true and there is a large proportion of fixed variable after the first model copy, remap all the model to a dense set of variable before the full presolve even starts. This should help for LNS on large models.
optional bool remove_fixed_variables_early = 310 [default = true];- Specified by:
hasRemoveFixedVariablesEarlyin interfaceSatParametersOrBuilder- Returns:
- Whether the removeFixedVariablesEarly field is set.
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getRemoveFixedVariablesEarly
public boolean getRemoveFixedVariablesEarly()If cp_model_presolve is true and there is a large proportion of fixed variable after the first model copy, remap all the model to a dense set of variable before the full presolve even starts. This should help for LNS on large models.
optional bool remove_fixed_variables_early = 310 [default = true];- Specified by:
getRemoveFixedVariablesEarlyin interfaceSatParametersOrBuilder- Returns:
- The removeFixedVariablesEarly.
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setRemoveFixedVariablesEarly
If cp_model_presolve is true and there is a large proportion of fixed variable after the first model copy, remap all the model to a dense set of variable before the full presolve even starts. This should help for LNS on large models.
optional bool remove_fixed_variables_early = 310 [default = true];- Parameters:
value- The removeFixedVariablesEarly to set.- Returns:
- This builder for chaining.
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clearRemoveFixedVariablesEarly
If cp_model_presolve is true and there is a large proportion of fixed variable after the first model copy, remap all the model to a dense set of variable before the full presolve even starts. This should help for LNS on large models.
optional bool remove_fixed_variables_early = 310 [default = true];- Returns:
- This builder for chaining.
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hasDetectTableWithCost
public boolean hasDetectTableWithCost()If true, we detect variable that are unique to a table constraint and only there to encode a cost on each tuple. This is usually the case when a WCSP (weighted constraint program) is encoded into CP-SAT format. This can lead to a dramatic speed-up for such problems but is still experimental at this point.
optional bool detect_table_with_cost = 216 [default = false];- Specified by:
hasDetectTableWithCostin interfaceSatParametersOrBuilder- Returns:
- Whether the detectTableWithCost field is set.
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getDetectTableWithCost
public boolean getDetectTableWithCost()If true, we detect variable that are unique to a table constraint and only there to encode a cost on each tuple. This is usually the case when a WCSP (weighted constraint program) is encoded into CP-SAT format. This can lead to a dramatic speed-up for such problems but is still experimental at this point.
optional bool detect_table_with_cost = 216 [default = false];- Specified by:
getDetectTableWithCostin interfaceSatParametersOrBuilder- Returns:
- The detectTableWithCost.
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setDetectTableWithCost
If true, we detect variable that are unique to a table constraint and only there to encode a cost on each tuple. This is usually the case when a WCSP (weighted constraint program) is encoded into CP-SAT format. This can lead to a dramatic speed-up for such problems but is still experimental at this point.
optional bool detect_table_with_cost = 216 [default = false];- Parameters:
value- The detectTableWithCost to set.- Returns:
- This builder for chaining.
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clearDetectTableWithCost
If true, we detect variable that are unique to a table constraint and only there to encode a cost on each tuple. This is usually the case when a WCSP (weighted constraint program) is encoded into CP-SAT format. This can lead to a dramatic speed-up for such problems but is still experimental at this point.
optional bool detect_table_with_cost = 216 [default = false];- Returns:
- This builder for chaining.
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hasTableCompressionLevel
public boolean hasTableCompressionLevel()How much we try to "compress" a table constraint. Compressing more leads to less Booleans and faster propagation but can reduced the quality of the lp relaxation. Values goes from 0 to 3 where we always try to fully compress a table. At 2, we try to automatically decide if it is worth it.
optional int32 table_compression_level = 217 [default = 2];- Specified by:
hasTableCompressionLevelin interfaceSatParametersOrBuilder- Returns:
- Whether the tableCompressionLevel field is set.
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getTableCompressionLevel
public int getTableCompressionLevel()How much we try to "compress" a table constraint. Compressing more leads to less Booleans and faster propagation but can reduced the quality of the lp relaxation. Values goes from 0 to 3 where we always try to fully compress a table. At 2, we try to automatically decide if it is worth it.
optional int32 table_compression_level = 217 [default = 2];- Specified by:
getTableCompressionLevelin interfaceSatParametersOrBuilder- Returns:
- The tableCompressionLevel.
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setTableCompressionLevel
How much we try to "compress" a table constraint. Compressing more leads to less Booleans and faster propagation but can reduced the quality of the lp relaxation. Values goes from 0 to 3 where we always try to fully compress a table. At 2, we try to automatically decide if it is worth it.
optional int32 table_compression_level = 217 [default = 2];- Parameters:
value- The tableCompressionLevel to set.- Returns:
- This builder for chaining.
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clearTableCompressionLevel
How much we try to "compress" a table constraint. Compressing more leads to less Booleans and faster propagation but can reduced the quality of the lp relaxation. Values goes from 0 to 3 where we always try to fully compress a table. At 2, we try to automatically decide if it is worth it.
optional int32 table_compression_level = 217 [default = 2];- Returns:
- This builder for chaining.
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hasExpandAlldiffConstraints
public boolean hasExpandAlldiffConstraints()If true, expand all_different constraints that are not permutations. Permutations (#Variables = #Values) are always expanded.
optional bool expand_alldiff_constraints = 170 [default = false];- Specified by:
hasExpandAlldiffConstraintsin interfaceSatParametersOrBuilder- Returns:
- Whether the expandAlldiffConstraints field is set.
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getExpandAlldiffConstraints
public boolean getExpandAlldiffConstraints()If true, expand all_different constraints that are not permutations. Permutations (#Variables = #Values) are always expanded.
optional bool expand_alldiff_constraints = 170 [default = false];- Specified by:
getExpandAlldiffConstraintsin interfaceSatParametersOrBuilder- Returns:
- The expandAlldiffConstraints.
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setExpandAlldiffConstraints
If true, expand all_different constraints that are not permutations. Permutations (#Variables = #Values) are always expanded.
optional bool expand_alldiff_constraints = 170 [default = false];- Parameters:
value- The expandAlldiffConstraints to set.- Returns:
- This builder for chaining.
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clearExpandAlldiffConstraints
If true, expand all_different constraints that are not permutations. Permutations (#Variables = #Values) are always expanded.
optional bool expand_alldiff_constraints = 170 [default = false];- Returns:
- This builder for chaining.
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hasMaxAlldiffDomainSize
public boolean hasMaxAlldiffDomainSize()Max domain size for all_different constraints to be expanded.
optional int32 max_alldiff_domain_size = 320 [default = 256];- Specified by:
hasMaxAlldiffDomainSizein interfaceSatParametersOrBuilder- Returns:
- Whether the maxAlldiffDomainSize field is set.
-
getMaxAlldiffDomainSize
public int getMaxAlldiffDomainSize()Max domain size for all_different constraints to be expanded.
optional int32 max_alldiff_domain_size = 320 [default = 256];- Specified by:
getMaxAlldiffDomainSizein interfaceSatParametersOrBuilder- Returns:
- The maxAlldiffDomainSize.
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setMaxAlldiffDomainSize
Max domain size for all_different constraints to be expanded.
optional int32 max_alldiff_domain_size = 320 [default = 256];- Parameters:
value- The maxAlldiffDomainSize to set.- Returns:
- This builder for chaining.
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clearMaxAlldiffDomainSize
Max domain size for all_different constraints to be expanded.
optional int32 max_alldiff_domain_size = 320 [default = 256];- Returns:
- This builder for chaining.
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hasExpandReservoirConstraints
public boolean hasExpandReservoirConstraints()If true, expand the reservoir constraints by creating booleans for all possible precedences between event and encoding the constraint.
optional bool expand_reservoir_constraints = 182 [default = true];- Specified by:
hasExpandReservoirConstraintsin interfaceSatParametersOrBuilder- Returns:
- Whether the expandReservoirConstraints field is set.
-
getExpandReservoirConstraints
public boolean getExpandReservoirConstraints()If true, expand the reservoir constraints by creating booleans for all possible precedences between event and encoding the constraint.
optional bool expand_reservoir_constraints = 182 [default = true];- Specified by:
getExpandReservoirConstraintsin interfaceSatParametersOrBuilder- Returns:
- The expandReservoirConstraints.
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setExpandReservoirConstraints
If true, expand the reservoir constraints by creating booleans for all possible precedences between event and encoding the constraint.
optional bool expand_reservoir_constraints = 182 [default = true];- Parameters:
value- The expandReservoirConstraints to set.- Returns:
- This builder for chaining.
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clearExpandReservoirConstraints
If true, expand the reservoir constraints by creating booleans for all possible precedences between event and encoding the constraint.
optional bool expand_reservoir_constraints = 182 [default = true];- Returns:
- This builder for chaining.
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hasMaxDomainSizeForLinear2Expansion
public boolean hasMaxDomainSizeForLinear2Expansion()Max domain size for expanding linear2 constraints (ax + by ==/!= c).
optional int32 max_domain_size_for_linear2_expansion = 340 [default = 8];- Specified by:
hasMaxDomainSizeForLinear2Expansionin interfaceSatParametersOrBuilder- Returns:
- Whether the maxDomainSizeForLinear2Expansion field is set.
-
getMaxDomainSizeForLinear2Expansion
public int getMaxDomainSizeForLinear2Expansion()Max domain size for expanding linear2 constraints (ax + by ==/!= c).
optional int32 max_domain_size_for_linear2_expansion = 340 [default = 8];- Specified by:
getMaxDomainSizeForLinear2Expansionin interfaceSatParametersOrBuilder- Returns:
- The maxDomainSizeForLinear2Expansion.
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setMaxDomainSizeForLinear2Expansion
Max domain size for expanding linear2 constraints (ax + by ==/!= c).
optional int32 max_domain_size_for_linear2_expansion = 340 [default = 8];- Parameters:
value- The maxDomainSizeForLinear2Expansion to set.- Returns:
- This builder for chaining.
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clearMaxDomainSizeForLinear2Expansion
Max domain size for expanding linear2 constraints (ax + by ==/!= c).
optional int32 max_domain_size_for_linear2_expansion = 340 [default = 8];- Returns:
- This builder for chaining.
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hasExpandReservoirUsingCircuit
public boolean hasExpandReservoirUsingCircuit()Mainly useful for testing. If this and expand_reservoir_constraints is true, we use a different encoding of the reservoir constraint using circuit instead of precedences. Note that this is usually slower, but can exercise different part of the solver. Note that contrary to the precedence encoding, this easily support variable demands. WARNING: with this encoding, the constraint takes a slightly different meaning. There must exist a permutation of the events occurring at the same time such that the level is within the reservoir after each of these events (in this permuted order). So we cannot have +100 and -100 at the same time if the level must be between 0 and 10 (as authorized by the reservoir constraint).
optional bool expand_reservoir_using_circuit = 288 [default = false];- Specified by:
hasExpandReservoirUsingCircuitin interfaceSatParametersOrBuilder- Returns:
- Whether the expandReservoirUsingCircuit field is set.
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getExpandReservoirUsingCircuit
public boolean getExpandReservoirUsingCircuit()Mainly useful for testing. If this and expand_reservoir_constraints is true, we use a different encoding of the reservoir constraint using circuit instead of precedences. Note that this is usually slower, but can exercise different part of the solver. Note that contrary to the precedence encoding, this easily support variable demands. WARNING: with this encoding, the constraint takes a slightly different meaning. There must exist a permutation of the events occurring at the same time such that the level is within the reservoir after each of these events (in this permuted order). So we cannot have +100 and -100 at the same time if the level must be between 0 and 10 (as authorized by the reservoir constraint).
optional bool expand_reservoir_using_circuit = 288 [default = false];- Specified by:
getExpandReservoirUsingCircuitin interfaceSatParametersOrBuilder- Returns:
- The expandReservoirUsingCircuit.
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setExpandReservoirUsingCircuit
Mainly useful for testing. If this and expand_reservoir_constraints is true, we use a different encoding of the reservoir constraint using circuit instead of precedences. Note that this is usually slower, but can exercise different part of the solver. Note that contrary to the precedence encoding, this easily support variable demands. WARNING: with this encoding, the constraint takes a slightly different meaning. There must exist a permutation of the events occurring at the same time such that the level is within the reservoir after each of these events (in this permuted order). So we cannot have +100 and -100 at the same time if the level must be between 0 and 10 (as authorized by the reservoir constraint).
optional bool expand_reservoir_using_circuit = 288 [default = false];- Parameters:
value- The expandReservoirUsingCircuit to set.- Returns:
- This builder for chaining.
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clearExpandReservoirUsingCircuit
Mainly useful for testing. If this and expand_reservoir_constraints is true, we use a different encoding of the reservoir constraint using circuit instead of precedences. Note that this is usually slower, but can exercise different part of the solver. Note that contrary to the precedence encoding, this easily support variable demands. WARNING: with this encoding, the constraint takes a slightly different meaning. There must exist a permutation of the events occurring at the same time such that the level is within the reservoir after each of these events (in this permuted order). So we cannot have +100 and -100 at the same time if the level must be between 0 and 10 (as authorized by the reservoir constraint).
optional bool expand_reservoir_using_circuit = 288 [default = false];- Returns:
- This builder for chaining.
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hasEncodeCumulativeAsReservoir
public boolean hasEncodeCumulativeAsReservoir()Encore cumulative with fixed demands and capacity as a reservoir constraint. The only reason you might want to do that is to test the reservoir propagation code!
optional bool encode_cumulative_as_reservoir = 287 [default = false];- Specified by:
hasEncodeCumulativeAsReservoirin interfaceSatParametersOrBuilder- Returns:
- Whether the encodeCumulativeAsReservoir field is set.
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getEncodeCumulativeAsReservoir
public boolean getEncodeCumulativeAsReservoir()Encore cumulative with fixed demands and capacity as a reservoir constraint. The only reason you might want to do that is to test the reservoir propagation code!
optional bool encode_cumulative_as_reservoir = 287 [default = false];- Specified by:
getEncodeCumulativeAsReservoirin interfaceSatParametersOrBuilder- Returns:
- The encodeCumulativeAsReservoir.
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setEncodeCumulativeAsReservoir
Encore cumulative with fixed demands and capacity as a reservoir constraint. The only reason you might want to do that is to test the reservoir propagation code!
optional bool encode_cumulative_as_reservoir = 287 [default = false];- Parameters:
value- The encodeCumulativeAsReservoir to set.- Returns:
- This builder for chaining.
-
clearEncodeCumulativeAsReservoir
Encore cumulative with fixed demands and capacity as a reservoir constraint. The only reason you might want to do that is to test the reservoir propagation code!
optional bool encode_cumulative_as_reservoir = 287 [default = false];- Returns:
- This builder for chaining.
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hasMaxLinMaxSizeForExpansion
public boolean hasMaxLinMaxSizeForExpansion()If the number of expressions in the lin_max is less that the max size parameter, model expansion replaces target = max(xi) by linear constraint with the introduction of new booleans bi such that bi => target == xi. This is mainly for experimenting compared to a custom lin_max propagator.
optional int32 max_lin_max_size_for_expansion = 280 [default = 0];- Specified by:
hasMaxLinMaxSizeForExpansionin interfaceSatParametersOrBuilder- Returns:
- Whether the maxLinMaxSizeForExpansion field is set.
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getMaxLinMaxSizeForExpansion
public int getMaxLinMaxSizeForExpansion()If the number of expressions in the lin_max is less that the max size parameter, model expansion replaces target = max(xi) by linear constraint with the introduction of new booleans bi such that bi => target == xi. This is mainly for experimenting compared to a custom lin_max propagator.
optional int32 max_lin_max_size_for_expansion = 280 [default = 0];- Specified by:
getMaxLinMaxSizeForExpansionin interfaceSatParametersOrBuilder- Returns:
- The maxLinMaxSizeForExpansion.
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setMaxLinMaxSizeForExpansion
If the number of expressions in the lin_max is less that the max size parameter, model expansion replaces target = max(xi) by linear constraint with the introduction of new booleans bi such that bi => target == xi. This is mainly for experimenting compared to a custom lin_max propagator.
optional int32 max_lin_max_size_for_expansion = 280 [default = 0];- Parameters:
value- The maxLinMaxSizeForExpansion to set.- Returns:
- This builder for chaining.
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clearMaxLinMaxSizeForExpansion
If the number of expressions in the lin_max is less that the max size parameter, model expansion replaces target = max(xi) by linear constraint with the introduction of new booleans bi such that bi => target == xi. This is mainly for experimenting compared to a custom lin_max propagator.
optional int32 max_lin_max_size_for_expansion = 280 [default = 0];- Returns:
- This builder for chaining.
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hasDisableConstraintExpansion
public boolean hasDisableConstraintExpansion()If true, it disable all constraint expansion. This should only be used to test the presolve of expanded constraints.
optional bool disable_constraint_expansion = 181 [default = false];- Specified by:
hasDisableConstraintExpansionin interfaceSatParametersOrBuilder- Returns:
- Whether the disableConstraintExpansion field is set.
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getDisableConstraintExpansion
public boolean getDisableConstraintExpansion()If true, it disable all constraint expansion. This should only be used to test the presolve of expanded constraints.
optional bool disable_constraint_expansion = 181 [default = false];- Specified by:
getDisableConstraintExpansionin interfaceSatParametersOrBuilder- Returns:
- The disableConstraintExpansion.
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setDisableConstraintExpansion
If true, it disable all constraint expansion. This should only be used to test the presolve of expanded constraints.
optional bool disable_constraint_expansion = 181 [default = false];- Parameters:
value- The disableConstraintExpansion to set.- Returns:
- This builder for chaining.
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clearDisableConstraintExpansion
If true, it disable all constraint expansion. This should only be used to test the presolve of expanded constraints.
optional bool disable_constraint_expansion = 181 [default = false];- Returns:
- This builder for chaining.
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hasEncodeComplexLinearConstraintWithInteger
public boolean hasEncodeComplexLinearConstraintWithInteger()Linear constraint with a complex right hand side (more than a single interval) need to be expanded, there is a couple of way to do that.
optional bool encode_complex_linear_constraint_with_integer = 223 [default = false];- Specified by:
hasEncodeComplexLinearConstraintWithIntegerin interfaceSatParametersOrBuilder- Returns:
- Whether the encodeComplexLinearConstraintWithInteger field is set.
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getEncodeComplexLinearConstraintWithInteger
public boolean getEncodeComplexLinearConstraintWithInteger()Linear constraint with a complex right hand side (more than a single interval) need to be expanded, there is a couple of way to do that.
optional bool encode_complex_linear_constraint_with_integer = 223 [default = false];- Specified by:
getEncodeComplexLinearConstraintWithIntegerin interfaceSatParametersOrBuilder- Returns:
- The encodeComplexLinearConstraintWithInteger.
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setEncodeComplexLinearConstraintWithInteger
Linear constraint with a complex right hand side (more than a single interval) need to be expanded, there is a couple of way to do that.
optional bool encode_complex_linear_constraint_with_integer = 223 [default = false];- Parameters:
value- The encodeComplexLinearConstraintWithInteger to set.- Returns:
- This builder for chaining.
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clearEncodeComplexLinearConstraintWithInteger
Linear constraint with a complex right hand side (more than a single interval) need to be expanded, there is a couple of way to do that.
optional bool encode_complex_linear_constraint_with_integer = 223 [default = false];- Returns:
- This builder for chaining.
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hasMergeNoOverlapWorkLimit
public boolean hasMergeNoOverlapWorkLimit()During presolve, we use a maximum clique heuristic to merge together no-overlap constraints or at most one constraints. This code can be slow, so we have a limit in place on the number of explored nodes in the underlying graph. The internal limit is an int64, but we use double here to simplify manual input.
optional double merge_no_overlap_work_limit = 145 [default = 1000000000000];- Specified by:
hasMergeNoOverlapWorkLimitin interfaceSatParametersOrBuilder- Returns:
- Whether the mergeNoOverlapWorkLimit field is set.
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getMergeNoOverlapWorkLimit
public double getMergeNoOverlapWorkLimit()During presolve, we use a maximum clique heuristic to merge together no-overlap constraints or at most one constraints. This code can be slow, so we have a limit in place on the number of explored nodes in the underlying graph. The internal limit is an int64, but we use double here to simplify manual input.
optional double merge_no_overlap_work_limit = 145 [default = 1000000000000];- Specified by:
getMergeNoOverlapWorkLimitin interfaceSatParametersOrBuilder- Returns:
- The mergeNoOverlapWorkLimit.
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setMergeNoOverlapWorkLimit
During presolve, we use a maximum clique heuristic to merge together no-overlap constraints or at most one constraints. This code can be slow, so we have a limit in place on the number of explored nodes in the underlying graph. The internal limit is an int64, but we use double here to simplify manual input.
optional double merge_no_overlap_work_limit = 145 [default = 1000000000000];- Parameters:
value- The mergeNoOverlapWorkLimit to set.- Returns:
- This builder for chaining.
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clearMergeNoOverlapWorkLimit
During presolve, we use a maximum clique heuristic to merge together no-overlap constraints or at most one constraints. This code can be slow, so we have a limit in place on the number of explored nodes in the underlying graph. The internal limit is an int64, but we use double here to simplify manual input.
optional double merge_no_overlap_work_limit = 145 [default = 1000000000000];- Returns:
- This builder for chaining.
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hasMergeAtMostOneWorkLimit
public boolean hasMergeAtMostOneWorkLimit()optional double merge_at_most_one_work_limit = 146 [default = 100000000];- Specified by:
hasMergeAtMostOneWorkLimitin interfaceSatParametersOrBuilder- Returns:
- Whether the mergeAtMostOneWorkLimit field is set.
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getMergeAtMostOneWorkLimit
public double getMergeAtMostOneWorkLimit()optional double merge_at_most_one_work_limit = 146 [default = 100000000];- Specified by:
getMergeAtMostOneWorkLimitin interfaceSatParametersOrBuilder- Returns:
- The mergeAtMostOneWorkLimit.
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setMergeAtMostOneWorkLimit
optional double merge_at_most_one_work_limit = 146 [default = 100000000];- Parameters:
value- The mergeAtMostOneWorkLimit to set.- Returns:
- This builder for chaining.
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clearMergeAtMostOneWorkLimit
optional double merge_at_most_one_work_limit = 146 [default = 100000000];- Returns:
- This builder for chaining.
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hasPresolveSubstitutionLevel
public boolean hasPresolveSubstitutionLevel()How much substitution (also called free variable aggregation in MIP litterature) should we perform at presolve. This currently only concerns variable appearing only in linear constraints. For now the value 0 turns it off and any positive value performs substitution.
optional int32 presolve_substitution_level = 147 [default = 1];- Specified by:
hasPresolveSubstitutionLevelin interfaceSatParametersOrBuilder- Returns:
- Whether the presolveSubstitutionLevel field is set.
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getPresolveSubstitutionLevel
public int getPresolveSubstitutionLevel()How much substitution (also called free variable aggregation in MIP litterature) should we perform at presolve. This currently only concerns variable appearing only in linear constraints. For now the value 0 turns it off and any positive value performs substitution.
optional int32 presolve_substitution_level = 147 [default = 1];- Specified by:
getPresolveSubstitutionLevelin interfaceSatParametersOrBuilder- Returns:
- The presolveSubstitutionLevel.
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setPresolveSubstitutionLevel
How much substitution (also called free variable aggregation in MIP litterature) should we perform at presolve. This currently only concerns variable appearing only in linear constraints. For now the value 0 turns it off and any positive value performs substitution.
optional int32 presolve_substitution_level = 147 [default = 1];- Parameters:
value- The presolveSubstitutionLevel to set.- Returns:
- This builder for chaining.
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clearPresolveSubstitutionLevel
How much substitution (also called free variable aggregation in MIP litterature) should we perform at presolve. This currently only concerns variable appearing only in linear constraints. For now the value 0 turns it off and any positive value performs substitution.
optional int32 presolve_substitution_level = 147 [default = 1];- Returns:
- This builder for chaining.
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hasPresolveExtractIntegerEnforcement
public boolean hasPresolveExtractIntegerEnforcement()If true, we will extract from linear constraints, enforcement literals of the form "integer variable at bound => simplified constraint". This should always be beneficial except that we don't always handle them as efficiently as we could for now. This causes problem on manna81.mps (LP relaxation not as tight it seems) and on neos-3354841-apure.mps.gz (too many literals created this way).
optional bool presolve_extract_integer_enforcement = 174 [default = false];- Specified by:
hasPresolveExtractIntegerEnforcementin interfaceSatParametersOrBuilder- Returns:
- Whether the presolveExtractIntegerEnforcement field is set.
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getPresolveExtractIntegerEnforcement
public boolean getPresolveExtractIntegerEnforcement()If true, we will extract from linear constraints, enforcement literals of the form "integer variable at bound => simplified constraint". This should always be beneficial except that we don't always handle them as efficiently as we could for now. This causes problem on manna81.mps (LP relaxation not as tight it seems) and on neos-3354841-apure.mps.gz (too many literals created this way).
optional bool presolve_extract_integer_enforcement = 174 [default = false];- Specified by:
getPresolveExtractIntegerEnforcementin interfaceSatParametersOrBuilder- Returns:
- The presolveExtractIntegerEnforcement.
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setPresolveExtractIntegerEnforcement
If true, we will extract from linear constraints, enforcement literals of the form "integer variable at bound => simplified constraint". This should always be beneficial except that we don't always handle them as efficiently as we could for now. This causes problem on manna81.mps (LP relaxation not as tight it seems) and on neos-3354841-apure.mps.gz (too many literals created this way).
optional bool presolve_extract_integer_enforcement = 174 [default = false];- Parameters:
value- The presolveExtractIntegerEnforcement to set.- Returns:
- This builder for chaining.
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clearPresolveExtractIntegerEnforcement
If true, we will extract from linear constraints, enforcement literals of the form "integer variable at bound => simplified constraint". This should always be beneficial except that we don't always handle them as efficiently as we could for now. This causes problem on manna81.mps (LP relaxation not as tight it seems) and on neos-3354841-apure.mps.gz (too many literals created this way).
optional bool presolve_extract_integer_enforcement = 174 [default = false];- Returns:
- This builder for chaining.
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hasPresolveInclusionWorkLimit
public boolean hasPresolveInclusionWorkLimit()A few presolve operations involve detecting constraints included in other constraint. Since there can be a quadratic number of such pairs, and processing them usually involve scanning them, the complexity of these operations can be big. This enforce a local deterministic limit on the number of entries scanned. Default is 1e8. A value of zero will disable these presolve rules completely.
optional int64 presolve_inclusion_work_limit = 201 [default = 100000000];- Specified by:
hasPresolveInclusionWorkLimitin interfaceSatParametersOrBuilder- Returns:
- Whether the presolveInclusionWorkLimit field is set.
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getPresolveInclusionWorkLimit
public long getPresolveInclusionWorkLimit()A few presolve operations involve detecting constraints included in other constraint. Since there can be a quadratic number of such pairs, and processing them usually involve scanning them, the complexity of these operations can be big. This enforce a local deterministic limit on the number of entries scanned. Default is 1e8. A value of zero will disable these presolve rules completely.
optional int64 presolve_inclusion_work_limit = 201 [default = 100000000];- Specified by:
getPresolveInclusionWorkLimitin interfaceSatParametersOrBuilder- Returns:
- The presolveInclusionWorkLimit.
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setPresolveInclusionWorkLimit
A few presolve operations involve detecting constraints included in other constraint. Since there can be a quadratic number of such pairs, and processing them usually involve scanning them, the complexity of these operations can be big. This enforce a local deterministic limit on the number of entries scanned. Default is 1e8. A value of zero will disable these presolve rules completely.
optional int64 presolve_inclusion_work_limit = 201 [default = 100000000];- Parameters:
value- The presolveInclusionWorkLimit to set.- Returns:
- This builder for chaining.
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clearPresolveInclusionWorkLimit
A few presolve operations involve detecting constraints included in other constraint. Since there can be a quadratic number of such pairs, and processing them usually involve scanning them, the complexity of these operations can be big. This enforce a local deterministic limit on the number of entries scanned. Default is 1e8. A value of zero will disable these presolve rules completely.
optional int64 presolve_inclusion_work_limit = 201 [default = 100000000];- Returns:
- This builder for chaining.
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hasIgnoreNames
public boolean hasIgnoreNames()If true, we don't keep names in our internal copy of the user given model.
optional bool ignore_names = 202 [default = true];- Specified by:
hasIgnoreNamesin interfaceSatParametersOrBuilder- Returns:
- Whether the ignoreNames field is set.
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getIgnoreNames
public boolean getIgnoreNames()If true, we don't keep names in our internal copy of the user given model.
optional bool ignore_names = 202 [default = true];- Specified by:
getIgnoreNamesin interfaceSatParametersOrBuilder- Returns:
- The ignoreNames.
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setIgnoreNames
If true, we don't keep names in our internal copy of the user given model.
optional bool ignore_names = 202 [default = true];- Parameters:
value- The ignoreNames to set.- Returns:
- This builder for chaining.
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clearIgnoreNames
If true, we don't keep names in our internal copy of the user given model.
optional bool ignore_names = 202 [default = true];- Returns:
- This builder for chaining.
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hasInferAllDiffs
public boolean hasInferAllDiffs()Run a max-clique code amongst all the x != y we can find and try to infer set of variables that are all different. This allows to close neos16.mps for instance. Note that we only run this code if there is no all_diff already in the model so that if a user want to add some all_diff, we assume it is well done and do not try to add more. This will also detect and add no_overlap constraints, if all the relations x != y have "offsets" between them. I.e. x > y + offset.
optional bool infer_all_diffs = 233 [default = true];- Specified by:
hasInferAllDiffsin interfaceSatParametersOrBuilder- Returns:
- Whether the inferAllDiffs field is set.
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getInferAllDiffs
public boolean getInferAllDiffs()Run a max-clique code amongst all the x != y we can find and try to infer set of variables that are all different. This allows to close neos16.mps for instance. Note that we only run this code if there is no all_diff already in the model so that if a user want to add some all_diff, we assume it is well done and do not try to add more. This will also detect and add no_overlap constraints, if all the relations x != y have "offsets" between them. I.e. x > y + offset.
optional bool infer_all_diffs = 233 [default = true];- Specified by:
getInferAllDiffsin interfaceSatParametersOrBuilder- Returns:
- The inferAllDiffs.
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setInferAllDiffs
Run a max-clique code amongst all the x != y we can find and try to infer set of variables that are all different. This allows to close neos16.mps for instance. Note that we only run this code if there is no all_diff already in the model so that if a user want to add some all_diff, we assume it is well done and do not try to add more. This will also detect and add no_overlap constraints, if all the relations x != y have "offsets" between them. I.e. x > y + offset.
optional bool infer_all_diffs = 233 [default = true];- Parameters:
value- The inferAllDiffs to set.- Returns:
- This builder for chaining.
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clearInferAllDiffs
Run a max-clique code amongst all the x != y we can find and try to infer set of variables that are all different. This allows to close neos16.mps for instance. Note that we only run this code if there is no all_diff already in the model so that if a user want to add some all_diff, we assume it is well done and do not try to add more. This will also detect and add no_overlap constraints, if all the relations x != y have "offsets" between them. I.e. x > y + offset.
optional bool infer_all_diffs = 233 [default = true];- Returns:
- This builder for chaining.
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hasFindBigLinearOverlap
public boolean hasFindBigLinearOverlap()Try to find large "rectangle" in the linear constraint matrix with identical lines. If such rectangle is big enough, we can introduce a new integer variable corresponding to the common expression and greatly reduce the number of non-zero.
optional bool find_big_linear_overlap = 234 [default = true];- Specified by:
hasFindBigLinearOverlapin interfaceSatParametersOrBuilder- Returns:
- Whether the findBigLinearOverlap field is set.
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getFindBigLinearOverlap
public boolean getFindBigLinearOverlap()Try to find large "rectangle" in the linear constraint matrix with identical lines. If such rectangle is big enough, we can introduce a new integer variable corresponding to the common expression and greatly reduce the number of non-zero.
optional bool find_big_linear_overlap = 234 [default = true];- Specified by:
getFindBigLinearOverlapin interfaceSatParametersOrBuilder- Returns:
- The findBigLinearOverlap.
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setFindBigLinearOverlap
Try to find large "rectangle" in the linear constraint matrix with identical lines. If such rectangle is big enough, we can introduce a new integer variable corresponding to the common expression and greatly reduce the number of non-zero.
optional bool find_big_linear_overlap = 234 [default = true];- Parameters:
value- The findBigLinearOverlap to set.- Returns:
- This builder for chaining.
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clearFindBigLinearOverlap
Try to find large "rectangle" in the linear constraint matrix with identical lines. If such rectangle is big enough, we can introduce a new integer variable corresponding to the common expression and greatly reduce the number of non-zero.
optional bool find_big_linear_overlap = 234 [default = true];- Returns:
- This builder for chaining.
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hasFindClausesThatAreExactlyOne
public boolean hasFindClausesThatAreExactlyOne()By propagating (or just using binary clauses), one can detect that all literal of a clause are actually in at most one relationship. Thus this constraint can be promoted to an exactly one constraints. This should help as it convey more structure. Note that this is expensive, so we have a deterministic limit in place.
optional bool find_clauses_that_are_exactly_one = 333 [default = true];- Specified by:
hasFindClausesThatAreExactlyOnein interfaceSatParametersOrBuilder- Returns:
- Whether the findClausesThatAreExactlyOne field is set.
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getFindClausesThatAreExactlyOne
public boolean getFindClausesThatAreExactlyOne()By propagating (or just using binary clauses), one can detect that all literal of a clause are actually in at most one relationship. Thus this constraint can be promoted to an exactly one constraints. This should help as it convey more structure. Note that this is expensive, so we have a deterministic limit in place.
optional bool find_clauses_that_are_exactly_one = 333 [default = true];- Specified by:
getFindClausesThatAreExactlyOnein interfaceSatParametersOrBuilder- Returns:
- The findClausesThatAreExactlyOne.
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setFindClausesThatAreExactlyOne
By propagating (or just using binary clauses), one can detect that all literal of a clause are actually in at most one relationship. Thus this constraint can be promoted to an exactly one constraints. This should help as it convey more structure. Note that this is expensive, so we have a deterministic limit in place.
optional bool find_clauses_that_are_exactly_one = 333 [default = true];- Parameters:
value- The findClausesThatAreExactlyOne to set.- Returns:
- This builder for chaining.
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clearFindClausesThatAreExactlyOne
By propagating (or just using binary clauses), one can detect that all literal of a clause are actually in at most one relationship. Thus this constraint can be promoted to an exactly one constraints. This should help as it convey more structure. Note that this is expensive, so we have a deterministic limit in place.
optional bool find_clauses_that_are_exactly_one = 333 [default = true];- Returns:
- This builder for chaining.
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hasUseSatInprocessing
public boolean hasUseSatInprocessing()Enable or disable "inprocessing" which is some SAT presolving done at each restart to the root level.
optional bool use_sat_inprocessing = 163 [default = true];- Specified by:
hasUseSatInprocessingin interfaceSatParametersOrBuilder- Returns:
- Whether the useSatInprocessing field is set.
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getUseSatInprocessing
public boolean getUseSatInprocessing()Enable or disable "inprocessing" which is some SAT presolving done at each restart to the root level.
optional bool use_sat_inprocessing = 163 [default = true];- Specified by:
getUseSatInprocessingin interfaceSatParametersOrBuilder- Returns:
- The useSatInprocessing.
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setUseSatInprocessing
Enable or disable "inprocessing" which is some SAT presolving done at each restart to the root level.
optional bool use_sat_inprocessing = 163 [default = true];- Parameters:
value- The useSatInprocessing to set.- Returns:
- This builder for chaining.
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clearUseSatInprocessing
Enable or disable "inprocessing" which is some SAT presolving done at each restart to the root level.
optional bool use_sat_inprocessing = 163 [default = true];- Returns:
- This builder for chaining.
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hasInprocessingDtimeRatio
public boolean hasInprocessingDtimeRatio()Proportion of deterministic time we should spend on inprocessing. At each "restart", if the proportion is below this ratio, we will do some inprocessing, otherwise, we skip it for this restart.
optional double inprocessing_dtime_ratio = 273 [default = 0.2];- Specified by:
hasInprocessingDtimeRatioin interfaceSatParametersOrBuilder- Returns:
- Whether the inprocessingDtimeRatio field is set.
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getInprocessingDtimeRatio
public double getInprocessingDtimeRatio()Proportion of deterministic time we should spend on inprocessing. At each "restart", if the proportion is below this ratio, we will do some inprocessing, otherwise, we skip it for this restart.
optional double inprocessing_dtime_ratio = 273 [default = 0.2];- Specified by:
getInprocessingDtimeRatioin interfaceSatParametersOrBuilder- Returns:
- The inprocessingDtimeRatio.
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setInprocessingDtimeRatio
Proportion of deterministic time we should spend on inprocessing. At each "restart", if the proportion is below this ratio, we will do some inprocessing, otherwise, we skip it for this restart.
optional double inprocessing_dtime_ratio = 273 [default = 0.2];- Parameters:
value- The inprocessingDtimeRatio to set.- Returns:
- This builder for chaining.
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clearInprocessingDtimeRatio
Proportion of deterministic time we should spend on inprocessing. At each "restart", if the proportion is below this ratio, we will do some inprocessing, otherwise, we skip it for this restart.
optional double inprocessing_dtime_ratio = 273 [default = 0.2];- Returns:
- This builder for chaining.
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hasInprocessingProbingDtime
public boolean hasInprocessingProbingDtime()The amount of dtime we should spend on probing for each inprocessing round.
optional double inprocessing_probing_dtime = 274 [default = 1];- Specified by:
hasInprocessingProbingDtimein interfaceSatParametersOrBuilder- Returns:
- Whether the inprocessingProbingDtime field is set.
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getInprocessingProbingDtime
public double getInprocessingProbingDtime()The amount of dtime we should spend on probing for each inprocessing round.
optional double inprocessing_probing_dtime = 274 [default = 1];- Specified by:
getInprocessingProbingDtimein interfaceSatParametersOrBuilder- Returns:
- The inprocessingProbingDtime.
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setInprocessingProbingDtime
The amount of dtime we should spend on probing for each inprocessing round.
optional double inprocessing_probing_dtime = 274 [default = 1];- Parameters:
value- The inprocessingProbingDtime to set.- Returns:
- This builder for chaining.
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clearInprocessingProbingDtime
The amount of dtime we should spend on probing for each inprocessing round.
optional double inprocessing_probing_dtime = 274 [default = 1];- Returns:
- This builder for chaining.
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hasInprocessingMinimizationDtime
public boolean hasInprocessingMinimizationDtime()Parameters for an heuristic similar to the one described in "An effective learnt clause minimization approach for CDCL Sat Solvers", https://www.ijcai.org/proceedings/2017/0098.pdf This is the amount of dtime we should spend on this technique during each inprocessing phase. The minimization technique is the same as the one used to minimize core in max-sat. We also minimize problem clauses and not just the learned clause that we keep forever like in the paper.
optional double inprocessing_minimization_dtime = 275 [default = 1];- Specified by:
hasInprocessingMinimizationDtimein interfaceSatParametersOrBuilder- Returns:
- Whether the inprocessingMinimizationDtime field is set.
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getInprocessingMinimizationDtime
public double getInprocessingMinimizationDtime()Parameters for an heuristic similar to the one described in "An effective learnt clause minimization approach for CDCL Sat Solvers", https://www.ijcai.org/proceedings/2017/0098.pdf This is the amount of dtime we should spend on this technique during each inprocessing phase. The minimization technique is the same as the one used to minimize core in max-sat. We also minimize problem clauses and not just the learned clause that we keep forever like in the paper.
optional double inprocessing_minimization_dtime = 275 [default = 1];- Specified by:
getInprocessingMinimizationDtimein interfaceSatParametersOrBuilder- Returns:
- The inprocessingMinimizationDtime.
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setInprocessingMinimizationDtime
Parameters for an heuristic similar to the one described in "An effective learnt clause minimization approach for CDCL Sat Solvers", https://www.ijcai.org/proceedings/2017/0098.pdf This is the amount of dtime we should spend on this technique during each inprocessing phase. The minimization technique is the same as the one used to minimize core in max-sat. We also minimize problem clauses and not just the learned clause that we keep forever like in the paper.
optional double inprocessing_minimization_dtime = 275 [default = 1];- Parameters:
value- The inprocessingMinimizationDtime to set.- Returns:
- This builder for chaining.
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clearInprocessingMinimizationDtime
Parameters for an heuristic similar to the one described in "An effective learnt clause minimization approach for CDCL Sat Solvers", https://www.ijcai.org/proceedings/2017/0098.pdf This is the amount of dtime we should spend on this technique during each inprocessing phase. The minimization technique is the same as the one used to minimize core in max-sat. We also minimize problem clauses and not just the learned clause that we keep forever like in the paper.
optional double inprocessing_minimization_dtime = 275 [default = 1];- Returns:
- This builder for chaining.
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hasInprocessingMinimizationUseConflictAnalysis
public boolean hasInprocessingMinimizationUseConflictAnalysis()optional bool inprocessing_minimization_use_conflict_analysis = 297 [default = true];- Specified by:
hasInprocessingMinimizationUseConflictAnalysisin interfaceSatParametersOrBuilder- Returns:
- Whether the inprocessingMinimizationUseConflictAnalysis field is set.
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getInprocessingMinimizationUseConflictAnalysis
public boolean getInprocessingMinimizationUseConflictAnalysis()optional bool inprocessing_minimization_use_conflict_analysis = 297 [default = true];- Specified by:
getInprocessingMinimizationUseConflictAnalysisin interfaceSatParametersOrBuilder- Returns:
- The inprocessingMinimizationUseConflictAnalysis.
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setInprocessingMinimizationUseConflictAnalysis
optional bool inprocessing_minimization_use_conflict_analysis = 297 [default = true];- Parameters:
value- The inprocessingMinimizationUseConflictAnalysis to set.- Returns:
- This builder for chaining.
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clearInprocessingMinimizationUseConflictAnalysis
optional bool inprocessing_minimization_use_conflict_analysis = 297 [default = true];- Returns:
- This builder for chaining.
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hasInprocessingMinimizationUseAllOrderings
public boolean hasInprocessingMinimizationUseAllOrderings()optional bool inprocessing_minimization_use_all_orderings = 298 [default = false];- Specified by:
hasInprocessingMinimizationUseAllOrderingsin interfaceSatParametersOrBuilder- Returns:
- Whether the inprocessingMinimizationUseAllOrderings field is set.
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getInprocessingMinimizationUseAllOrderings
public boolean getInprocessingMinimizationUseAllOrderings()optional bool inprocessing_minimization_use_all_orderings = 298 [default = false];- Specified by:
getInprocessingMinimizationUseAllOrderingsin interfaceSatParametersOrBuilder- Returns:
- The inprocessingMinimizationUseAllOrderings.
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setInprocessingMinimizationUseAllOrderings
optional bool inprocessing_minimization_use_all_orderings = 298 [default = false];- Parameters:
value- The inprocessingMinimizationUseAllOrderings to set.- Returns:
- This builder for chaining.
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clearInprocessingMinimizationUseAllOrderings
optional bool inprocessing_minimization_use_all_orderings = 298 [default = false];- Returns:
- This builder for chaining.
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hasInprocessingUseCongruenceClosure
public boolean hasInprocessingUseCongruenceClosure()Whether we use the algorithm described in "Clausal Congruence closure", Armin Biere, Katalin Fazekas, Mathias Fleury, Nils Froleyks, 2024. Note that we only have a basic version currently.
optional bool inprocessing_use_congruence_closure = 342 [default = true];- Specified by:
hasInprocessingUseCongruenceClosurein interfaceSatParametersOrBuilder- Returns:
- Whether the inprocessingUseCongruenceClosure field is set.
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getInprocessingUseCongruenceClosure
public boolean getInprocessingUseCongruenceClosure()Whether we use the algorithm described in "Clausal Congruence closure", Armin Biere, Katalin Fazekas, Mathias Fleury, Nils Froleyks, 2024. Note that we only have a basic version currently.
optional bool inprocessing_use_congruence_closure = 342 [default = true];- Specified by:
getInprocessingUseCongruenceClosurein interfaceSatParametersOrBuilder- Returns:
- The inprocessingUseCongruenceClosure.
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setInprocessingUseCongruenceClosure
Whether we use the algorithm described in "Clausal Congruence closure", Armin Biere, Katalin Fazekas, Mathias Fleury, Nils Froleyks, 2024. Note that we only have a basic version currently.
optional bool inprocessing_use_congruence_closure = 342 [default = true];- Parameters:
value- The inprocessingUseCongruenceClosure to set.- Returns:
- This builder for chaining.
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clearInprocessingUseCongruenceClosure
Whether we use the algorithm described in "Clausal Congruence closure", Armin Biere, Katalin Fazekas, Mathias Fleury, Nils Froleyks, 2024. Note that we only have a basic version currently.
optional bool inprocessing_use_congruence_closure = 342 [default = true];- Returns:
- This builder for chaining.
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hasInprocessingUseSatSweeping
public boolean hasInprocessingUseSatSweeping()Whether we use the SAT sweeping algorithm described in "Clausal Equivalence Sweeping", Armin Biere, Katalin Fazekas, Mathias Fleury, Nils Froleyks, 2025.
optional bool inprocessing_use_sat_sweeping = 354 [default = false];- Specified by:
hasInprocessingUseSatSweepingin interfaceSatParametersOrBuilder- Returns:
- Whether the inprocessingUseSatSweeping field is set.
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getInprocessingUseSatSweeping
public boolean getInprocessingUseSatSweeping()Whether we use the SAT sweeping algorithm described in "Clausal Equivalence Sweeping", Armin Biere, Katalin Fazekas, Mathias Fleury, Nils Froleyks, 2025.
optional bool inprocessing_use_sat_sweeping = 354 [default = false];- Specified by:
getInprocessingUseSatSweepingin interfaceSatParametersOrBuilder- Returns:
- The inprocessingUseSatSweeping.
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setInprocessingUseSatSweeping
Whether we use the SAT sweeping algorithm described in "Clausal Equivalence Sweeping", Armin Biere, Katalin Fazekas, Mathias Fleury, Nils Froleyks, 2025.
optional bool inprocessing_use_sat_sweeping = 354 [default = false];- Parameters:
value- The inprocessingUseSatSweeping to set.- Returns:
- This builder for chaining.
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clearInprocessingUseSatSweeping
Whether we use the SAT sweeping algorithm described in "Clausal Equivalence Sweeping", Armin Biere, Katalin Fazekas, Mathias Fleury, Nils Froleyks, 2025.
optional bool inprocessing_use_sat_sweeping = 354 [default = false];- Returns:
- This builder for chaining.
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hasNumWorkers
public boolean hasNumWorkers()Specify the number of parallel workers (i.e. threads) to use during search. This should usually be lower than your number of available cpus + hyperthread in your machine. A value of 0 means the solver will try to use all cores on the machine. A number of 1 means no parallelism. Note that 'num_workers' is the preferred name, but if it is set to zero, we will still read the deprecated 'num_search_workers'. As of 2020-04-10, if you're using SAT via MPSolver (to solve integer programs) this field is overridden with a value of 8, if the field is not set *explicitly*. Thus, always set this field explicitly or via MPSolver::SetNumThreads().
optional int32 num_workers = 206 [default = 0];- Specified by:
hasNumWorkersin interfaceSatParametersOrBuilder- Returns:
- Whether the numWorkers field is set.
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getNumWorkers
public int getNumWorkers()Specify the number of parallel workers (i.e. threads) to use during search. This should usually be lower than your number of available cpus + hyperthread in your machine. A value of 0 means the solver will try to use all cores on the machine. A number of 1 means no parallelism. Note that 'num_workers' is the preferred name, but if it is set to zero, we will still read the deprecated 'num_search_workers'. As of 2020-04-10, if you're using SAT via MPSolver (to solve integer programs) this field is overridden with a value of 8, if the field is not set *explicitly*. Thus, always set this field explicitly or via MPSolver::SetNumThreads().
optional int32 num_workers = 206 [default = 0];- Specified by:
getNumWorkersin interfaceSatParametersOrBuilder- Returns:
- The numWorkers.
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setNumWorkers
Specify the number of parallel workers (i.e. threads) to use during search. This should usually be lower than your number of available cpus + hyperthread in your machine. A value of 0 means the solver will try to use all cores on the machine. A number of 1 means no parallelism. Note that 'num_workers' is the preferred name, but if it is set to zero, we will still read the deprecated 'num_search_workers'. As of 2020-04-10, if you're using SAT via MPSolver (to solve integer programs) this field is overridden with a value of 8, if the field is not set *explicitly*. Thus, always set this field explicitly or via MPSolver::SetNumThreads().
optional int32 num_workers = 206 [default = 0];- Parameters:
value- The numWorkers to set.- Returns:
- This builder for chaining.
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clearNumWorkers
Specify the number of parallel workers (i.e. threads) to use during search. This should usually be lower than your number of available cpus + hyperthread in your machine. A value of 0 means the solver will try to use all cores on the machine. A number of 1 means no parallelism. Note that 'num_workers' is the preferred name, but if it is set to zero, we will still read the deprecated 'num_search_workers'. As of 2020-04-10, if you're using SAT via MPSolver (to solve integer programs) this field is overridden with a value of 8, if the field is not set *explicitly*. Thus, always set this field explicitly or via MPSolver::SetNumThreads().
optional int32 num_workers = 206 [default = 0];- Returns:
- This builder for chaining.
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hasNumSearchWorkers
public boolean hasNumSearchWorkers()optional int32 num_search_workers = 100 [default = 0];- Specified by:
hasNumSearchWorkersin interfaceSatParametersOrBuilder- Returns:
- Whether the numSearchWorkers field is set.
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getNumSearchWorkers
public int getNumSearchWorkers()optional int32 num_search_workers = 100 [default = 0];- Specified by:
getNumSearchWorkersin interfaceSatParametersOrBuilder- Returns:
- The numSearchWorkers.
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setNumSearchWorkers
optional int32 num_search_workers = 100 [default = 0];- Parameters:
value- The numSearchWorkers to set.- Returns:
- This builder for chaining.
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clearNumSearchWorkers
optional int32 num_search_workers = 100 [default = 0];- Returns:
- This builder for chaining.
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hasNumFullSubsolvers
public boolean hasNumFullSubsolvers()We distinguish subsolvers that consume a full thread, and the ones that are always interleaved. If left at zero, we will fix this with a default formula that depends on num_workers. But if you start modifying what runs, you might want to fix that to a given value depending on the num_workers you use.
optional int32 num_full_subsolvers = 294 [default = 0];- Specified by:
hasNumFullSubsolversin interfaceSatParametersOrBuilder- Returns:
- Whether the numFullSubsolvers field is set.
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getNumFullSubsolvers
public int getNumFullSubsolvers()We distinguish subsolvers that consume a full thread, and the ones that are always interleaved. If left at zero, we will fix this with a default formula that depends on num_workers. But if you start modifying what runs, you might want to fix that to a given value depending on the num_workers you use.
optional int32 num_full_subsolvers = 294 [default = 0];- Specified by:
getNumFullSubsolversin interfaceSatParametersOrBuilder- Returns:
- The numFullSubsolvers.
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setNumFullSubsolvers
We distinguish subsolvers that consume a full thread, and the ones that are always interleaved. If left at zero, we will fix this with a default formula that depends on num_workers. But if you start modifying what runs, you might want to fix that to a given value depending on the num_workers you use.
optional int32 num_full_subsolvers = 294 [default = 0];- Parameters:
value- The numFullSubsolvers to set.- Returns:
- This builder for chaining.
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clearNumFullSubsolvers
We distinguish subsolvers that consume a full thread, and the ones that are always interleaved. If left at zero, we will fix this with a default formula that depends on num_workers. But if you start modifying what runs, you might want to fix that to a given value depending on the num_workers you use.
optional int32 num_full_subsolvers = 294 [default = 0];- Returns:
- This builder for chaining.
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getSubsolversList
public com.google.protobuf.ProtocolStringList getSubsolversList()In multi-thread, the solver can be mainly seen as a portfolio of solvers with different parameters. This field indicates the names of the parameters that are used in multithread. This only applies to "full" subsolvers. See cp_model_search.cc to see a list of the names and the default value (if left empty) that looks like: - default_lp (linearization_level:1) - fixed (only if fixed search specified or scheduling) - no_lp (linearization_level:0) - max_lp (linearization_level:2) - pseudo_costs (only if objective, change search heuristic) - reduced_costs (only if objective, change search heuristic) - quick_restart (kind of probing) - quick_restart_no_lp (kind of probing with linearization_level:0) - lb_tree_search (to improve lower bound, MIP like tree search) - probing (continuous probing and shaving) Also, note that some set of parameters will be ignored if they do not make sense. For instance if there is no objective, pseudo_cost or reduced_cost search will be ignored. Core based search will only work if the objective has many terms. If there is no fixed strategy fixed will be ignored. And so on. The order is important, as only the first num_full_subsolvers will be scheduled. You can see in the log which one are selected for a given run.
repeated string subsolvers = 207;- Specified by:
getSubsolversListin interfaceSatParametersOrBuilder- Returns:
- A list containing the subsolvers.
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getSubsolversCount
public int getSubsolversCount()In multi-thread, the solver can be mainly seen as a portfolio of solvers with different parameters. This field indicates the names of the parameters that are used in multithread. This only applies to "full" subsolvers. See cp_model_search.cc to see a list of the names and the default value (if left empty) that looks like: - default_lp (linearization_level:1) - fixed (only if fixed search specified or scheduling) - no_lp (linearization_level:0) - max_lp (linearization_level:2) - pseudo_costs (only if objective, change search heuristic) - reduced_costs (only if objective, change search heuristic) - quick_restart (kind of probing) - quick_restart_no_lp (kind of probing with linearization_level:0) - lb_tree_search (to improve lower bound, MIP like tree search) - probing (continuous probing and shaving) Also, note that some set of parameters will be ignored if they do not make sense. For instance if there is no objective, pseudo_cost or reduced_cost search will be ignored. Core based search will only work if the objective has many terms. If there is no fixed strategy fixed will be ignored. And so on. The order is important, as only the first num_full_subsolvers will be scheduled. You can see in the log which one are selected for a given run.
repeated string subsolvers = 207;- Specified by:
getSubsolversCountin interfaceSatParametersOrBuilder- Returns:
- The count of subsolvers.
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getSubsolvers
In multi-thread, the solver can be mainly seen as a portfolio of solvers with different parameters. This field indicates the names of the parameters that are used in multithread. This only applies to "full" subsolvers. See cp_model_search.cc to see a list of the names and the default value (if left empty) that looks like: - default_lp (linearization_level:1) - fixed (only if fixed search specified or scheduling) - no_lp (linearization_level:0) - max_lp (linearization_level:2) - pseudo_costs (only if objective, change search heuristic) - reduced_costs (only if objective, change search heuristic) - quick_restart (kind of probing) - quick_restart_no_lp (kind of probing with linearization_level:0) - lb_tree_search (to improve lower bound, MIP like tree search) - probing (continuous probing and shaving) Also, note that some set of parameters will be ignored if they do not make sense. For instance if there is no objective, pseudo_cost or reduced_cost search will be ignored. Core based search will only work if the objective has many terms. If there is no fixed strategy fixed will be ignored. And so on. The order is important, as only the first num_full_subsolvers will be scheduled. You can see in the log which one are selected for a given run.
repeated string subsolvers = 207;- Specified by:
getSubsolversin interfaceSatParametersOrBuilder- Parameters:
index- The index of the element to return.- Returns:
- The subsolvers at the given index.
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getSubsolversBytes
public com.google.protobuf.ByteString getSubsolversBytes(int index) In multi-thread, the solver can be mainly seen as a portfolio of solvers with different parameters. This field indicates the names of the parameters that are used in multithread. This only applies to "full" subsolvers. See cp_model_search.cc to see a list of the names and the default value (if left empty) that looks like: - default_lp (linearization_level:1) - fixed (only if fixed search specified or scheduling) - no_lp (linearization_level:0) - max_lp (linearization_level:2) - pseudo_costs (only if objective, change search heuristic) - reduced_costs (only if objective, change search heuristic) - quick_restart (kind of probing) - quick_restart_no_lp (kind of probing with linearization_level:0) - lb_tree_search (to improve lower bound, MIP like tree search) - probing (continuous probing and shaving) Also, note that some set of parameters will be ignored if they do not make sense. For instance if there is no objective, pseudo_cost or reduced_cost search will be ignored. Core based search will only work if the objective has many terms. If there is no fixed strategy fixed will be ignored. And so on. The order is important, as only the first num_full_subsolvers will be scheduled. You can see in the log which one are selected for a given run.
repeated string subsolvers = 207;- Specified by:
getSubsolversBytesin interfaceSatParametersOrBuilder- Parameters:
index- The index of the value to return.- Returns:
- The bytes of the subsolvers at the given index.
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setSubsolvers
In multi-thread, the solver can be mainly seen as a portfolio of solvers with different parameters. This field indicates the names of the parameters that are used in multithread. This only applies to "full" subsolvers. See cp_model_search.cc to see a list of the names and the default value (if left empty) that looks like: - default_lp (linearization_level:1) - fixed (only if fixed search specified or scheduling) - no_lp (linearization_level:0) - max_lp (linearization_level:2) - pseudo_costs (only if objective, change search heuristic) - reduced_costs (only if objective, change search heuristic) - quick_restart (kind of probing) - quick_restart_no_lp (kind of probing with linearization_level:0) - lb_tree_search (to improve lower bound, MIP like tree search) - probing (continuous probing and shaving) Also, note that some set of parameters will be ignored if they do not make sense. For instance if there is no objective, pseudo_cost or reduced_cost search will be ignored. Core based search will only work if the objective has many terms. If there is no fixed strategy fixed will be ignored. And so on. The order is important, as only the first num_full_subsolvers will be scheduled. You can see in the log which one are selected for a given run.
repeated string subsolvers = 207;- Parameters:
index- The index to set the value at.value- The subsolvers to set.- Returns:
- This builder for chaining.
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addSubsolvers
In multi-thread, the solver can be mainly seen as a portfolio of solvers with different parameters. This field indicates the names of the parameters that are used in multithread. This only applies to "full" subsolvers. See cp_model_search.cc to see a list of the names and the default value (if left empty) that looks like: - default_lp (linearization_level:1) - fixed (only if fixed search specified or scheduling) - no_lp (linearization_level:0) - max_lp (linearization_level:2) - pseudo_costs (only if objective, change search heuristic) - reduced_costs (only if objective, change search heuristic) - quick_restart (kind of probing) - quick_restart_no_lp (kind of probing with linearization_level:0) - lb_tree_search (to improve lower bound, MIP like tree search) - probing (continuous probing and shaving) Also, note that some set of parameters will be ignored if they do not make sense. For instance if there is no objective, pseudo_cost or reduced_cost search will be ignored. Core based search will only work if the objective has many terms. If there is no fixed strategy fixed will be ignored. And so on. The order is important, as only the first num_full_subsolvers will be scheduled. You can see in the log which one are selected for a given run.
repeated string subsolvers = 207;- Parameters:
value- The subsolvers to add.- Returns:
- This builder for chaining.
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addAllSubsolvers
In multi-thread, the solver can be mainly seen as a portfolio of solvers with different parameters. This field indicates the names of the parameters that are used in multithread. This only applies to "full" subsolvers. See cp_model_search.cc to see a list of the names and the default value (if left empty) that looks like: - default_lp (linearization_level:1) - fixed (only if fixed search specified or scheduling) - no_lp (linearization_level:0) - max_lp (linearization_level:2) - pseudo_costs (only if objective, change search heuristic) - reduced_costs (only if objective, change search heuristic) - quick_restart (kind of probing) - quick_restart_no_lp (kind of probing with linearization_level:0) - lb_tree_search (to improve lower bound, MIP like tree search) - probing (continuous probing and shaving) Also, note that some set of parameters will be ignored if they do not make sense. For instance if there is no objective, pseudo_cost or reduced_cost search will be ignored. Core based search will only work if the objective has many terms. If there is no fixed strategy fixed will be ignored. And so on. The order is important, as only the first num_full_subsolvers will be scheduled. You can see in the log which one are selected for a given run.
repeated string subsolvers = 207;- Parameters:
values- The subsolvers to add.- Returns:
- This builder for chaining.
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clearSubsolvers
In multi-thread, the solver can be mainly seen as a portfolio of solvers with different parameters. This field indicates the names of the parameters that are used in multithread. This only applies to "full" subsolvers. See cp_model_search.cc to see a list of the names and the default value (if left empty) that looks like: - default_lp (linearization_level:1) - fixed (only if fixed search specified or scheduling) - no_lp (linearization_level:0) - max_lp (linearization_level:2) - pseudo_costs (only if objective, change search heuristic) - reduced_costs (only if objective, change search heuristic) - quick_restart (kind of probing) - quick_restart_no_lp (kind of probing with linearization_level:0) - lb_tree_search (to improve lower bound, MIP like tree search) - probing (continuous probing and shaving) Also, note that some set of parameters will be ignored if they do not make sense. For instance if there is no objective, pseudo_cost or reduced_cost search will be ignored. Core based search will only work if the objective has many terms. If there is no fixed strategy fixed will be ignored. And so on. The order is important, as only the first num_full_subsolvers will be scheduled. You can see in the log which one are selected for a given run.
repeated string subsolvers = 207;- Returns:
- This builder for chaining.
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addSubsolversBytes
In multi-thread, the solver can be mainly seen as a portfolio of solvers with different parameters. This field indicates the names of the parameters that are used in multithread. This only applies to "full" subsolvers. See cp_model_search.cc to see a list of the names and the default value (if left empty) that looks like: - default_lp (linearization_level:1) - fixed (only if fixed search specified or scheduling) - no_lp (linearization_level:0) - max_lp (linearization_level:2) - pseudo_costs (only if objective, change search heuristic) - reduced_costs (only if objective, change search heuristic) - quick_restart (kind of probing) - quick_restart_no_lp (kind of probing with linearization_level:0) - lb_tree_search (to improve lower bound, MIP like tree search) - probing (continuous probing and shaving) Also, note that some set of parameters will be ignored if they do not make sense. For instance if there is no objective, pseudo_cost or reduced_cost search will be ignored. Core based search will only work if the objective has many terms. If there is no fixed strategy fixed will be ignored. And so on. The order is important, as only the first num_full_subsolvers will be scheduled. You can see in the log which one are selected for a given run.
repeated string subsolvers = 207;- Parameters:
value- The bytes of the subsolvers to add.- Returns:
- This builder for chaining.
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getExtraSubsolversList
public com.google.protobuf.ProtocolStringList getExtraSubsolversList()A convenient way to add more workers types. These will be added at the beginning of the list.
repeated string extra_subsolvers = 219;- Specified by:
getExtraSubsolversListin interfaceSatParametersOrBuilder- Returns:
- A list containing the extraSubsolvers.
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getExtraSubsolversCount
public int getExtraSubsolversCount()A convenient way to add more workers types. These will be added at the beginning of the list.
repeated string extra_subsolvers = 219;- Specified by:
getExtraSubsolversCountin interfaceSatParametersOrBuilder- Returns:
- The count of extraSubsolvers.
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getExtraSubsolvers
A convenient way to add more workers types. These will be added at the beginning of the list.
repeated string extra_subsolvers = 219;- Specified by:
getExtraSubsolversin interfaceSatParametersOrBuilder- Parameters:
index- The index of the element to return.- Returns:
- The extraSubsolvers at the given index.
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getExtraSubsolversBytes
public com.google.protobuf.ByteString getExtraSubsolversBytes(int index) A convenient way to add more workers types. These will be added at the beginning of the list.
repeated string extra_subsolvers = 219;- Specified by:
getExtraSubsolversBytesin interfaceSatParametersOrBuilder- Parameters:
index- The index of the value to return.- Returns:
- The bytes of the extraSubsolvers at the given index.
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setExtraSubsolvers
A convenient way to add more workers types. These will be added at the beginning of the list.
repeated string extra_subsolvers = 219;- Parameters:
index- The index to set the value at.value- The extraSubsolvers to set.- Returns:
- This builder for chaining.
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addExtraSubsolvers
A convenient way to add more workers types. These will be added at the beginning of the list.
repeated string extra_subsolvers = 219;- Parameters:
value- The extraSubsolvers to add.- Returns:
- This builder for chaining.
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addAllExtraSubsolvers
A convenient way to add more workers types. These will be added at the beginning of the list.
repeated string extra_subsolvers = 219;- Parameters:
values- The extraSubsolvers to add.- Returns:
- This builder for chaining.
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clearExtraSubsolvers
A convenient way to add more workers types. These will be added at the beginning of the list.
repeated string extra_subsolvers = 219;- Returns:
- This builder for chaining.
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addExtraSubsolversBytes
A convenient way to add more workers types. These will be added at the beginning of the list.
repeated string extra_subsolvers = 219;- Parameters:
value- The bytes of the extraSubsolvers to add.- Returns:
- This builder for chaining.
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getIgnoreSubsolversList
public com.google.protobuf.ProtocolStringList getIgnoreSubsolversList()Rather than fully specifying subsolvers, it is often convenient to just remove the ones that are not useful on a given problem or only keep specific ones for testing. Each string is interpreted as a "glob", so we support '*' and '?'. The way this work is that we will only accept a name that match a filter pattern (if non-empty) and do not match an ignore pattern. Note also that these fields work on LNS or LS names even if these are currently not specified via the subsolvers field.
repeated string ignore_subsolvers = 209;- Specified by:
getIgnoreSubsolversListin interfaceSatParametersOrBuilder- Returns:
- A list containing the ignoreSubsolvers.
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getIgnoreSubsolversCount
public int getIgnoreSubsolversCount()Rather than fully specifying subsolvers, it is often convenient to just remove the ones that are not useful on a given problem or only keep specific ones for testing. Each string is interpreted as a "glob", so we support '*' and '?'. The way this work is that we will only accept a name that match a filter pattern (if non-empty) and do not match an ignore pattern. Note also that these fields work on LNS or LS names even if these are currently not specified via the subsolvers field.
repeated string ignore_subsolvers = 209;- Specified by:
getIgnoreSubsolversCountin interfaceSatParametersOrBuilder- Returns:
- The count of ignoreSubsolvers.
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getIgnoreSubsolvers
Rather than fully specifying subsolvers, it is often convenient to just remove the ones that are not useful on a given problem or only keep specific ones for testing. Each string is interpreted as a "glob", so we support '*' and '?'. The way this work is that we will only accept a name that match a filter pattern (if non-empty) and do not match an ignore pattern. Note also that these fields work on LNS or LS names even if these are currently not specified via the subsolvers field.
repeated string ignore_subsolvers = 209;- Specified by:
getIgnoreSubsolversin interfaceSatParametersOrBuilder- Parameters:
index- The index of the element to return.- Returns:
- The ignoreSubsolvers at the given index.
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getIgnoreSubsolversBytes
public com.google.protobuf.ByteString getIgnoreSubsolversBytes(int index) Rather than fully specifying subsolvers, it is often convenient to just remove the ones that are not useful on a given problem or only keep specific ones for testing. Each string is interpreted as a "glob", so we support '*' and '?'. The way this work is that we will only accept a name that match a filter pattern (if non-empty) and do not match an ignore pattern. Note also that these fields work on LNS or LS names even if these are currently not specified via the subsolvers field.
repeated string ignore_subsolvers = 209;- Specified by:
getIgnoreSubsolversBytesin interfaceSatParametersOrBuilder- Parameters:
index- The index of the value to return.- Returns:
- The bytes of the ignoreSubsolvers at the given index.
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setIgnoreSubsolvers
Rather than fully specifying subsolvers, it is often convenient to just remove the ones that are not useful on a given problem or only keep specific ones for testing. Each string is interpreted as a "glob", so we support '*' and '?'. The way this work is that we will only accept a name that match a filter pattern (if non-empty) and do not match an ignore pattern. Note also that these fields work on LNS or LS names even if these are currently not specified via the subsolvers field.
repeated string ignore_subsolvers = 209;- Parameters:
index- The index to set the value at.value- The ignoreSubsolvers to set.- Returns:
- This builder for chaining.
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addIgnoreSubsolvers
Rather than fully specifying subsolvers, it is often convenient to just remove the ones that are not useful on a given problem or only keep specific ones for testing. Each string is interpreted as a "glob", so we support '*' and '?'. The way this work is that we will only accept a name that match a filter pattern (if non-empty) and do not match an ignore pattern. Note also that these fields work on LNS or LS names even if these are currently not specified via the subsolvers field.
repeated string ignore_subsolvers = 209;- Parameters:
value- The ignoreSubsolvers to add.- Returns:
- This builder for chaining.
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addAllIgnoreSubsolvers
Rather than fully specifying subsolvers, it is often convenient to just remove the ones that are not useful on a given problem or only keep specific ones for testing. Each string is interpreted as a "glob", so we support '*' and '?'. The way this work is that we will only accept a name that match a filter pattern (if non-empty) and do not match an ignore pattern. Note also that these fields work on LNS or LS names even if these are currently not specified via the subsolvers field.
repeated string ignore_subsolvers = 209;- Parameters:
values- The ignoreSubsolvers to add.- Returns:
- This builder for chaining.
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clearIgnoreSubsolvers
Rather than fully specifying subsolvers, it is often convenient to just remove the ones that are not useful on a given problem or only keep specific ones for testing. Each string is interpreted as a "glob", so we support '*' and '?'. The way this work is that we will only accept a name that match a filter pattern (if non-empty) and do not match an ignore pattern. Note also that these fields work on LNS or LS names even if these are currently not specified via the subsolvers field.
repeated string ignore_subsolvers = 209;- Returns:
- This builder for chaining.
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addIgnoreSubsolversBytes
Rather than fully specifying subsolvers, it is often convenient to just remove the ones that are not useful on a given problem or only keep specific ones for testing. Each string is interpreted as a "glob", so we support '*' and '?'. The way this work is that we will only accept a name that match a filter pattern (if non-empty) and do not match an ignore pattern. Note also that these fields work on LNS or LS names even if these are currently not specified via the subsolvers field.
repeated string ignore_subsolvers = 209;- Parameters:
value- The bytes of the ignoreSubsolvers to add.- Returns:
- This builder for chaining.
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getFilterSubsolversList
public com.google.protobuf.ProtocolStringList getFilterSubsolversList()repeated string filter_subsolvers = 293;- Specified by:
getFilterSubsolversListin interfaceSatParametersOrBuilder- Returns:
- A list containing the filterSubsolvers.
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getFilterSubsolversCount
public int getFilterSubsolversCount()repeated string filter_subsolvers = 293;- Specified by:
getFilterSubsolversCountin interfaceSatParametersOrBuilder- Returns:
- The count of filterSubsolvers.
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getFilterSubsolvers
repeated string filter_subsolvers = 293;- Specified by:
getFilterSubsolversin interfaceSatParametersOrBuilder- Parameters:
index- The index of the element to return.- Returns:
- The filterSubsolvers at the given index.
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getFilterSubsolversBytes
public com.google.protobuf.ByteString getFilterSubsolversBytes(int index) repeated string filter_subsolvers = 293;- Specified by:
getFilterSubsolversBytesin interfaceSatParametersOrBuilder- Parameters:
index- The index of the value to return.- Returns:
- The bytes of the filterSubsolvers at the given index.
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setFilterSubsolvers
repeated string filter_subsolvers = 293;- Parameters:
index- The index to set the value at.value- The filterSubsolvers to set.- Returns:
- This builder for chaining.
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addFilterSubsolvers
repeated string filter_subsolvers = 293;- Parameters:
value- The filterSubsolvers to add.- Returns:
- This builder for chaining.
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addAllFilterSubsolvers
repeated string filter_subsolvers = 293;- Parameters:
values- The filterSubsolvers to add.- Returns:
- This builder for chaining.
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clearFilterSubsolvers
repeated string filter_subsolvers = 293;- Returns:
- This builder for chaining.
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addFilterSubsolversBytes
repeated string filter_subsolvers = 293;- Parameters:
value- The bytes of the filterSubsolvers to add.- Returns:
- This builder for chaining.
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getSubsolverParamsList
It is possible to specify additional subsolver configuration. These can be referred by their params.name() in the fields above. Note that only the specified field will "overwrite" the ones of the base parameter. If a subsolver_params has the name of an existing subsolver configuration, the named parameters will be merged into the subsolver configuration.
repeated .operations_research.sat.SatParameters subsolver_params = 210;- Specified by:
getSubsolverParamsListin interfaceSatParametersOrBuilder
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getSubsolverParamsCount
public int getSubsolverParamsCount()It is possible to specify additional subsolver configuration. These can be referred by their params.name() in the fields above. Note that only the specified field will "overwrite" the ones of the base parameter. If a subsolver_params has the name of an existing subsolver configuration, the named parameters will be merged into the subsolver configuration.
repeated .operations_research.sat.SatParameters subsolver_params = 210;- Specified by:
getSubsolverParamsCountin interfaceSatParametersOrBuilder
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getSubsolverParams
It is possible to specify additional subsolver configuration. These can be referred by their params.name() in the fields above. Note that only the specified field will "overwrite" the ones of the base parameter. If a subsolver_params has the name of an existing subsolver configuration, the named parameters will be merged into the subsolver configuration.
repeated .operations_research.sat.SatParameters subsolver_params = 210;- Specified by:
getSubsolverParamsin interfaceSatParametersOrBuilder
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setSubsolverParams
It is possible to specify additional subsolver configuration. These can be referred by their params.name() in the fields above. Note that only the specified field will "overwrite" the ones of the base parameter. If a subsolver_params has the name of an existing subsolver configuration, the named parameters will be merged into the subsolver configuration.
repeated .operations_research.sat.SatParameters subsolver_params = 210; -
setSubsolverParams
It is possible to specify additional subsolver configuration. These can be referred by their params.name() in the fields above. Note that only the specified field will "overwrite" the ones of the base parameter. If a subsolver_params has the name of an existing subsolver configuration, the named parameters will be merged into the subsolver configuration.
repeated .operations_research.sat.SatParameters subsolver_params = 210; -
addSubsolverParams
It is possible to specify additional subsolver configuration. These can be referred by their params.name() in the fields above. Note that only the specified field will "overwrite" the ones of the base parameter. If a subsolver_params has the name of an existing subsolver configuration, the named parameters will be merged into the subsolver configuration.
repeated .operations_research.sat.SatParameters subsolver_params = 210; -
addSubsolverParams
It is possible to specify additional subsolver configuration. These can be referred by their params.name() in the fields above. Note that only the specified field will "overwrite" the ones of the base parameter. If a subsolver_params has the name of an existing subsolver configuration, the named parameters will be merged into the subsolver configuration.
repeated .operations_research.sat.SatParameters subsolver_params = 210; -
addSubsolverParams
It is possible to specify additional subsolver configuration. These can be referred by their params.name() in the fields above. Note that only the specified field will "overwrite" the ones of the base parameter. If a subsolver_params has the name of an existing subsolver configuration, the named parameters will be merged into the subsolver configuration.
repeated .operations_research.sat.SatParameters subsolver_params = 210; -
addSubsolverParams
It is possible to specify additional subsolver configuration. These can be referred by their params.name() in the fields above. Note that only the specified field will "overwrite" the ones of the base parameter. If a subsolver_params has the name of an existing subsolver configuration, the named parameters will be merged into the subsolver configuration.
repeated .operations_research.sat.SatParameters subsolver_params = 210; -
addAllSubsolverParams
It is possible to specify additional subsolver configuration. These can be referred by their params.name() in the fields above. Note that only the specified field will "overwrite" the ones of the base parameter. If a subsolver_params has the name of an existing subsolver configuration, the named parameters will be merged into the subsolver configuration.
repeated .operations_research.sat.SatParameters subsolver_params = 210; -
clearSubsolverParams
It is possible to specify additional subsolver configuration. These can be referred by their params.name() in the fields above. Note that only the specified field will "overwrite" the ones of the base parameter. If a subsolver_params has the name of an existing subsolver configuration, the named parameters will be merged into the subsolver configuration.
repeated .operations_research.sat.SatParameters subsolver_params = 210; -
removeSubsolverParams
It is possible to specify additional subsolver configuration. These can be referred by their params.name() in the fields above. Note that only the specified field will "overwrite" the ones of the base parameter. If a subsolver_params has the name of an existing subsolver configuration, the named parameters will be merged into the subsolver configuration.
repeated .operations_research.sat.SatParameters subsolver_params = 210; -
getSubsolverParamsBuilder
It is possible to specify additional subsolver configuration. These can be referred by their params.name() in the fields above. Note that only the specified field will "overwrite" the ones of the base parameter. If a subsolver_params has the name of an existing subsolver configuration, the named parameters will be merged into the subsolver configuration.
repeated .operations_research.sat.SatParameters subsolver_params = 210; -
getSubsolverParamsOrBuilder
It is possible to specify additional subsolver configuration. These can be referred by their params.name() in the fields above. Note that only the specified field will "overwrite" the ones of the base parameter. If a subsolver_params has the name of an existing subsolver configuration, the named parameters will be merged into the subsolver configuration.
repeated .operations_research.sat.SatParameters subsolver_params = 210;- Specified by:
getSubsolverParamsOrBuilderin interfaceSatParametersOrBuilder
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getSubsolverParamsOrBuilderList
It is possible to specify additional subsolver configuration. These can be referred by their params.name() in the fields above. Note that only the specified field will "overwrite" the ones of the base parameter. If a subsolver_params has the name of an existing subsolver configuration, the named parameters will be merged into the subsolver configuration.
repeated .operations_research.sat.SatParameters subsolver_params = 210;- Specified by:
getSubsolverParamsOrBuilderListin interfaceSatParametersOrBuilder
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addSubsolverParamsBuilder
It is possible to specify additional subsolver configuration. These can be referred by their params.name() in the fields above. Note that only the specified field will "overwrite" the ones of the base parameter. If a subsolver_params has the name of an existing subsolver configuration, the named parameters will be merged into the subsolver configuration.
repeated .operations_research.sat.SatParameters subsolver_params = 210; -
addSubsolverParamsBuilder
It is possible to specify additional subsolver configuration. These can be referred by their params.name() in the fields above. Note that only the specified field will "overwrite" the ones of the base parameter. If a subsolver_params has the name of an existing subsolver configuration, the named parameters will be merged into the subsolver configuration.
repeated .operations_research.sat.SatParameters subsolver_params = 210; -
getSubsolverParamsBuilderList
It is possible to specify additional subsolver configuration. These can be referred by their params.name() in the fields above. Note that only the specified field will "overwrite" the ones of the base parameter. If a subsolver_params has the name of an existing subsolver configuration, the named parameters will be merged into the subsolver configuration.
repeated .operations_research.sat.SatParameters subsolver_params = 210; -
hasInterleaveSearch
public boolean hasInterleaveSearch()Experimental. If this is true, then we interleave all our major search strategy and distribute the work amongst num_workers. The search is deterministic (independently of num_workers!), and we schedule and wait for interleave_batch_size task to be completed before synchronizing and scheduling the next batch of tasks.
optional bool interleave_search = 136 [default = false];- Specified by:
hasInterleaveSearchin interfaceSatParametersOrBuilder- Returns:
- Whether the interleaveSearch field is set.
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getInterleaveSearch
public boolean getInterleaveSearch()Experimental. If this is true, then we interleave all our major search strategy and distribute the work amongst num_workers. The search is deterministic (independently of num_workers!), and we schedule and wait for interleave_batch_size task to be completed before synchronizing and scheduling the next batch of tasks.
optional bool interleave_search = 136 [default = false];- Specified by:
getInterleaveSearchin interfaceSatParametersOrBuilder- Returns:
- The interleaveSearch.
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setInterleaveSearch
Experimental. If this is true, then we interleave all our major search strategy and distribute the work amongst num_workers. The search is deterministic (independently of num_workers!), and we schedule and wait for interleave_batch_size task to be completed before synchronizing and scheduling the next batch of tasks.
optional bool interleave_search = 136 [default = false];- Parameters:
value- The interleaveSearch to set.- Returns:
- This builder for chaining.
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clearInterleaveSearch
Experimental. If this is true, then we interleave all our major search strategy and distribute the work amongst num_workers. The search is deterministic (independently of num_workers!), and we schedule and wait for interleave_batch_size task to be completed before synchronizing and scheduling the next batch of tasks.
optional bool interleave_search = 136 [default = false];- Returns:
- This builder for chaining.
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hasInterleaveBatchSize
public boolean hasInterleaveBatchSize()optional int32 interleave_batch_size = 134 [default = 0];- Specified by:
hasInterleaveBatchSizein interfaceSatParametersOrBuilder- Returns:
- Whether the interleaveBatchSize field is set.
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getInterleaveBatchSize
public int getInterleaveBatchSize()optional int32 interleave_batch_size = 134 [default = 0];- Specified by:
getInterleaveBatchSizein interfaceSatParametersOrBuilder- Returns:
- The interleaveBatchSize.
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setInterleaveBatchSize
optional int32 interleave_batch_size = 134 [default = 0];- Parameters:
value- The interleaveBatchSize to set.- Returns:
- This builder for chaining.
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clearInterleaveBatchSize
optional int32 interleave_batch_size = 134 [default = 0];- Returns:
- This builder for chaining.
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hasCheckLratProof
public boolean hasCheckLratProof()If true, inferred clauses are checked with an LRAT checker as they are learned, in presolve (reduced to trivial simplifications if cp_model_presolve is false), and in each worker. As of December 2025, this only works with pure SAT problems, with - cp_model_presolve = false, - linearization_level <= 1, - symmetry_level <= 1.
optional bool check_lrat_proof = 344 [default = false];- Specified by:
hasCheckLratProofin interfaceSatParametersOrBuilder- Returns:
- Whether the checkLratProof field is set.
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getCheckLratProof
public boolean getCheckLratProof()If true, inferred clauses are checked with an LRAT checker as they are learned, in presolve (reduced to trivial simplifications if cp_model_presolve is false), and in each worker. As of December 2025, this only works with pure SAT problems, with - cp_model_presolve = false, - linearization_level <= 1, - symmetry_level <= 1.
optional bool check_lrat_proof = 344 [default = false];- Specified by:
getCheckLratProofin interfaceSatParametersOrBuilder- Returns:
- The checkLratProof.
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setCheckLratProof
If true, inferred clauses are checked with an LRAT checker as they are learned, in presolve (reduced to trivial simplifications if cp_model_presolve is false), and in each worker. As of December 2025, this only works with pure SAT problems, with - cp_model_presolve = false, - linearization_level <= 1, - symmetry_level <= 1.
optional bool check_lrat_proof = 344 [default = false];- Parameters:
value- The checkLratProof to set.- Returns:
- This builder for chaining.
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clearCheckLratProof
If true, inferred clauses are checked with an LRAT checker as they are learned, in presolve (reduced to trivial simplifications if cp_model_presolve is false), and in each worker. As of December 2025, this only works with pure SAT problems, with - cp_model_presolve = false, - linearization_level <= 1, - symmetry_level <= 1.
optional bool check_lrat_proof = 344 [default = false];- Returns:
- This builder for chaining.
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hasCheckMergedLratProof
public boolean hasCheckMergedLratProof()If true, and if output_lrat_proof is true and the problem is UNSAT, check that the merged proof file is valid, i.e., that clause sharing between workers is correct. This checks each inferred clause, so you might want to disable check_lrat_proof to avoid redundant work. As of November 2025, this only works for pure SAT problems, with num_workers = 1.
optional bool check_merged_lrat_proof = 352 [default = false];- Specified by:
hasCheckMergedLratProofin interfaceSatParametersOrBuilder- Returns:
- Whether the checkMergedLratProof field is set.
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getCheckMergedLratProof
public boolean getCheckMergedLratProof()If true, and if output_lrat_proof is true and the problem is UNSAT, check that the merged proof file is valid, i.e., that clause sharing between workers is correct. This checks each inferred clause, so you might want to disable check_lrat_proof to avoid redundant work. As of November 2025, this only works for pure SAT problems, with num_workers = 1.
optional bool check_merged_lrat_proof = 352 [default = false];- Specified by:
getCheckMergedLratProofin interfaceSatParametersOrBuilder- Returns:
- The checkMergedLratProof.
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setCheckMergedLratProof
If true, and if output_lrat_proof is true and the problem is UNSAT, check that the merged proof file is valid, i.e., that clause sharing between workers is correct. This checks each inferred clause, so you might want to disable check_lrat_proof to avoid redundant work. As of November 2025, this only works for pure SAT problems, with num_workers = 1.
optional bool check_merged_lrat_proof = 352 [default = false];- Parameters:
value- The checkMergedLratProof to set.- Returns:
- This builder for chaining.
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clearCheckMergedLratProof
If true, and if output_lrat_proof is true and the problem is UNSAT, check that the merged proof file is valid, i.e., that clause sharing between workers is correct. This checks each inferred clause, so you might want to disable check_lrat_proof to avoid redundant work. As of November 2025, this only works for pure SAT problems, with num_workers = 1.
optional bool check_merged_lrat_proof = 352 [default = false];- Returns:
- This builder for chaining.
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hasOutputLratProof
public boolean hasOutputLratProof()If true, an LRAT proof that all the clauses inferred by the solver are valid is output to several files (one for presolve -- reduced to trivial simplifications if cp_model_presolve is false, one per worker, and one for the merged proof). As of December 2025, this only works for pure SAT problems, with - cp_model_presolve = false, - linearization_level <= 1, - symmetry_level <= 1.
optional bool output_lrat_proof = 345 [default = false];- Specified by:
hasOutputLratProofin interfaceSatParametersOrBuilder- Returns:
- Whether the outputLratProof field is set.
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getOutputLratProof
public boolean getOutputLratProof()If true, an LRAT proof that all the clauses inferred by the solver are valid is output to several files (one for presolve -- reduced to trivial simplifications if cp_model_presolve is false, one per worker, and one for the merged proof). As of December 2025, this only works for pure SAT problems, with - cp_model_presolve = false, - linearization_level <= 1, - symmetry_level <= 1.
optional bool output_lrat_proof = 345 [default = false];- Specified by:
getOutputLratProofin interfaceSatParametersOrBuilder- Returns:
- The outputLratProof.
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setOutputLratProof
If true, an LRAT proof that all the clauses inferred by the solver are valid is output to several files (one for presolve -- reduced to trivial simplifications if cp_model_presolve is false, one per worker, and one for the merged proof). As of December 2025, this only works for pure SAT problems, with - cp_model_presolve = false, - linearization_level <= 1, - symmetry_level <= 1.
optional bool output_lrat_proof = 345 [default = false];- Parameters:
value- The outputLratProof to set.- Returns:
- This builder for chaining.
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clearOutputLratProof
If true, an LRAT proof that all the clauses inferred by the solver are valid is output to several files (one for presolve -- reduced to trivial simplifications if cp_model_presolve is false, one per worker, and one for the merged proof). As of December 2025, this only works for pure SAT problems, with - cp_model_presolve = false, - linearization_level <= 1, - symmetry_level <= 1.
optional bool output_lrat_proof = 345 [default = false];- Returns:
- This builder for chaining.
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hasCheckDratProof
public boolean hasCheckDratProof()If true, and if the problem is UNSAT, a DRAT proof of this UNSAT property is checked after the solver has finished. As of November 2025, this only works for pure SAT problems, with - num_workers = 1, - cp_model_presolve = false, - linearization_level <= 1, - symmetry_level <= 1.
optional bool check_drat_proof = 346 [default = false];- Specified by:
hasCheckDratProofin interfaceSatParametersOrBuilder- Returns:
- Whether the checkDratProof field is set.
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getCheckDratProof
public boolean getCheckDratProof()If true, and if the problem is UNSAT, a DRAT proof of this UNSAT property is checked after the solver has finished. As of November 2025, this only works for pure SAT problems, with - num_workers = 1, - cp_model_presolve = false, - linearization_level <= 1, - symmetry_level <= 1.
optional bool check_drat_proof = 346 [default = false];- Specified by:
getCheckDratProofin interfaceSatParametersOrBuilder- Returns:
- The checkDratProof.
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setCheckDratProof
If true, and if the problem is UNSAT, a DRAT proof of this UNSAT property is checked after the solver has finished. As of November 2025, this only works for pure SAT problems, with - num_workers = 1, - cp_model_presolve = false, - linearization_level <= 1, - symmetry_level <= 1.
optional bool check_drat_proof = 346 [default = false];- Parameters:
value- The checkDratProof to set.- Returns:
- This builder for chaining.
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clearCheckDratProof
If true, and if the problem is UNSAT, a DRAT proof of this UNSAT property is checked after the solver has finished. As of November 2025, this only works for pure SAT problems, with - num_workers = 1, - cp_model_presolve = false, - linearization_level <= 1, - symmetry_level <= 1.
optional bool check_drat_proof = 346 [default = false];- Returns:
- This builder for chaining.
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hasOutputDratProof
public boolean hasOutputDratProof()If true, a DRAT proof that all the clauses inferred by the solver are valid is output to a file. As of December 2025, this only works for pure SAT problems, with - num_workers = 1, - cp_model_presolve = false, - linearization_level <= 1, - symmetry_level <= 1.
optional bool output_drat_proof = 347 [default = false];- Specified by:
hasOutputDratProofin interfaceSatParametersOrBuilder- Returns:
- Whether the outputDratProof field is set.
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getOutputDratProof
public boolean getOutputDratProof()If true, a DRAT proof that all the clauses inferred by the solver are valid is output to a file. As of December 2025, this only works for pure SAT problems, with - num_workers = 1, - cp_model_presolve = false, - linearization_level <= 1, - symmetry_level <= 1.
optional bool output_drat_proof = 347 [default = false];- Specified by:
getOutputDratProofin interfaceSatParametersOrBuilder- Returns:
- The outputDratProof.
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setOutputDratProof
If true, a DRAT proof that all the clauses inferred by the solver are valid is output to a file. As of December 2025, this only works for pure SAT problems, with - num_workers = 1, - cp_model_presolve = false, - linearization_level <= 1, - symmetry_level <= 1.
optional bool output_drat_proof = 347 [default = false];- Parameters:
value- The outputDratProof to set.- Returns:
- This builder for chaining.
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clearOutputDratProof
If true, a DRAT proof that all the clauses inferred by the solver are valid is output to a file. As of December 2025, this only works for pure SAT problems, with - num_workers = 1, - cp_model_presolve = false, - linearization_level <= 1, - symmetry_level <= 1.
optional bool output_drat_proof = 347 [default = false];- Returns:
- This builder for chaining.
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hasMaxDratTimeInSeconds
public boolean hasMaxDratTimeInSeconds()The maximum time allowed to check the DRAT proof (this can take more time than the solve itself). Only used if check_drat_proof is true.
optional double max_drat_time_in_seconds = 348 [default = inf];- Specified by:
hasMaxDratTimeInSecondsin interfaceSatParametersOrBuilder- Returns:
- Whether the maxDratTimeInSeconds field is set.
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getMaxDratTimeInSeconds
public double getMaxDratTimeInSeconds()The maximum time allowed to check the DRAT proof (this can take more time than the solve itself). Only used if check_drat_proof is true.
optional double max_drat_time_in_seconds = 348 [default = inf];- Specified by:
getMaxDratTimeInSecondsin interfaceSatParametersOrBuilder- Returns:
- The maxDratTimeInSeconds.
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setMaxDratTimeInSeconds
The maximum time allowed to check the DRAT proof (this can take more time than the solve itself). Only used if check_drat_proof is true.
optional double max_drat_time_in_seconds = 348 [default = inf];- Parameters:
value- The maxDratTimeInSeconds to set.- Returns:
- This builder for chaining.
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clearMaxDratTimeInSeconds
The maximum time allowed to check the DRAT proof (this can take more time than the solve itself). Only used if check_drat_proof is true.
optional double max_drat_time_in_seconds = 348 [default = inf];- Returns:
- This builder for chaining.
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hasDebugPostsolveWithFullSolver
public boolean hasDebugPostsolveWithFullSolver()We have two different postsolve code. The default one should be better and it allows for a more powerful presolve, but it can be useful to postsolve using the full solver instead.
optional bool debug_postsolve_with_full_solver = 162 [default = false];- Specified by:
hasDebugPostsolveWithFullSolverin interfaceSatParametersOrBuilder- Returns:
- Whether the debugPostsolveWithFullSolver field is set.
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getDebugPostsolveWithFullSolver
public boolean getDebugPostsolveWithFullSolver()We have two different postsolve code. The default one should be better and it allows for a more powerful presolve, but it can be useful to postsolve using the full solver instead.
optional bool debug_postsolve_with_full_solver = 162 [default = false];- Specified by:
getDebugPostsolveWithFullSolverin interfaceSatParametersOrBuilder- Returns:
- The debugPostsolveWithFullSolver.
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setDebugPostsolveWithFullSolver
We have two different postsolve code. The default one should be better and it allows for a more powerful presolve, but it can be useful to postsolve using the full solver instead.
optional bool debug_postsolve_with_full_solver = 162 [default = false];- Parameters:
value- The debugPostsolveWithFullSolver to set.- Returns:
- This builder for chaining.
-
clearDebugPostsolveWithFullSolver
We have two different postsolve code. The default one should be better and it allows for a more powerful presolve, but it can be useful to postsolve using the full solver instead.
optional bool debug_postsolve_with_full_solver = 162 [default = false];- Returns:
- This builder for chaining.
-
hasDebugMaxNumPresolveOperations
public boolean hasDebugMaxNumPresolveOperations()If positive, try to stop just after that many presolve rules have been applied. This is mainly useful for debugging presolve.
optional int32 debug_max_num_presolve_operations = 151 [default = 0];- Specified by:
hasDebugMaxNumPresolveOperationsin interfaceSatParametersOrBuilder- Returns:
- Whether the debugMaxNumPresolveOperations field is set.
-
getDebugMaxNumPresolveOperations
public int getDebugMaxNumPresolveOperations()If positive, try to stop just after that many presolve rules have been applied. This is mainly useful for debugging presolve.
optional int32 debug_max_num_presolve_operations = 151 [default = 0];- Specified by:
getDebugMaxNumPresolveOperationsin interfaceSatParametersOrBuilder- Returns:
- The debugMaxNumPresolveOperations.
-
setDebugMaxNumPresolveOperations
If positive, try to stop just after that many presolve rules have been applied. This is mainly useful for debugging presolve.
optional int32 debug_max_num_presolve_operations = 151 [default = 0];- Parameters:
value- The debugMaxNumPresolveOperations to set.- Returns:
- This builder for chaining.
-
clearDebugMaxNumPresolveOperations
If positive, try to stop just after that many presolve rules have been applied. This is mainly useful for debugging presolve.
optional int32 debug_max_num_presolve_operations = 151 [default = 0];- Returns:
- This builder for chaining.
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hasDebugCrashOnBadHint
public boolean hasDebugCrashOnBadHint()Crash if we do not manage to complete the hint into a full solution.
optional bool debug_crash_on_bad_hint = 195 [default = false];- Specified by:
hasDebugCrashOnBadHintin interfaceSatParametersOrBuilder- Returns:
- Whether the debugCrashOnBadHint field is set.
-
getDebugCrashOnBadHint
public boolean getDebugCrashOnBadHint()Crash if we do not manage to complete the hint into a full solution.
optional bool debug_crash_on_bad_hint = 195 [default = false];- Specified by:
getDebugCrashOnBadHintin interfaceSatParametersOrBuilder- Returns:
- The debugCrashOnBadHint.
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setDebugCrashOnBadHint
Crash if we do not manage to complete the hint into a full solution.
optional bool debug_crash_on_bad_hint = 195 [default = false];- Parameters:
value- The debugCrashOnBadHint to set.- Returns:
- This builder for chaining.
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clearDebugCrashOnBadHint
Crash if we do not manage to complete the hint into a full solution.
optional bool debug_crash_on_bad_hint = 195 [default = false];- Returns:
- This builder for chaining.
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hasDebugCrashIfPresolveBreaksHint
public boolean hasDebugCrashIfPresolveBreaksHint()Crash if presolve breaks a feasible hint.
optional bool debug_crash_if_presolve_breaks_hint = 306 [default = false];- Specified by:
hasDebugCrashIfPresolveBreaksHintin interfaceSatParametersOrBuilder- Returns:
- Whether the debugCrashIfPresolveBreaksHint field is set.
-
getDebugCrashIfPresolveBreaksHint
public boolean getDebugCrashIfPresolveBreaksHint()Crash if presolve breaks a feasible hint.
optional bool debug_crash_if_presolve_breaks_hint = 306 [default = false];- Specified by:
getDebugCrashIfPresolveBreaksHintin interfaceSatParametersOrBuilder- Returns:
- The debugCrashIfPresolveBreaksHint.
-
setDebugCrashIfPresolveBreaksHint
Crash if presolve breaks a feasible hint.
optional bool debug_crash_if_presolve_breaks_hint = 306 [default = false];- Parameters:
value- The debugCrashIfPresolveBreaksHint to set.- Returns:
- This builder for chaining.
-
clearDebugCrashIfPresolveBreaksHint
Crash if presolve breaks a feasible hint.
optional bool debug_crash_if_presolve_breaks_hint = 306 [default = false];- Returns:
- This builder for chaining.
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hasDebugCrashIfLratCheckFails
public boolean hasDebugCrashIfLratCheckFails()Crash if the LRAT UNSAT proof is invalid.
optional bool debug_crash_if_lrat_check_fails = 339 [default = false];- Specified by:
hasDebugCrashIfLratCheckFailsin interfaceSatParametersOrBuilder- Returns:
- Whether the debugCrashIfLratCheckFails field is set.
-
getDebugCrashIfLratCheckFails
public boolean getDebugCrashIfLratCheckFails()Crash if the LRAT UNSAT proof is invalid.
optional bool debug_crash_if_lrat_check_fails = 339 [default = false];- Specified by:
getDebugCrashIfLratCheckFailsin interfaceSatParametersOrBuilder- Returns:
- The debugCrashIfLratCheckFails.
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setDebugCrashIfLratCheckFails
Crash if the LRAT UNSAT proof is invalid.
optional bool debug_crash_if_lrat_check_fails = 339 [default = false];- Parameters:
value- The debugCrashIfLratCheckFails to set.- Returns:
- This builder for chaining.
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clearDebugCrashIfLratCheckFails
Crash if the LRAT UNSAT proof is invalid.
optional bool debug_crash_if_lrat_check_fails = 339 [default = false];- Returns:
- This builder for chaining.
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hasUseOptimizationHints
public boolean hasUseOptimizationHints()For an optimization problem, whether we follow some hints in order to find a better first solution. For a variable with hint, the solver will always try to follow the hint. It will revert to the variable_branching default otherwise.
optional bool use_optimization_hints = 35 [default = true];- Specified by:
hasUseOptimizationHintsin interfaceSatParametersOrBuilder- Returns:
- Whether the useOptimizationHints field is set.
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getUseOptimizationHints
public boolean getUseOptimizationHints()For an optimization problem, whether we follow some hints in order to find a better first solution. For a variable with hint, the solver will always try to follow the hint. It will revert to the variable_branching default otherwise.
optional bool use_optimization_hints = 35 [default = true];- Specified by:
getUseOptimizationHintsin interfaceSatParametersOrBuilder- Returns:
- The useOptimizationHints.
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setUseOptimizationHints
For an optimization problem, whether we follow some hints in order to find a better first solution. For a variable with hint, the solver will always try to follow the hint. It will revert to the variable_branching default otherwise.
optional bool use_optimization_hints = 35 [default = true];- Parameters:
value- The useOptimizationHints to set.- Returns:
- This builder for chaining.
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clearUseOptimizationHints
For an optimization problem, whether we follow some hints in order to find a better first solution. For a variable with hint, the solver will always try to follow the hint. It will revert to the variable_branching default otherwise.
optional bool use_optimization_hints = 35 [default = true];- Returns:
- This builder for chaining.
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hasCoreMinimizationLevel
public boolean hasCoreMinimizationLevel()If positive, we spend some effort on each core: - At level 1, we use a simple heuristic to try to minimize an UNSAT core. - At level 2, we use propagation to minimize the core but also identify literal in at most one relationship in this core.
optional int32 core_minimization_level = 50 [default = 2];- Specified by:
hasCoreMinimizationLevelin interfaceSatParametersOrBuilder- Returns:
- Whether the coreMinimizationLevel field is set.
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getCoreMinimizationLevel
public int getCoreMinimizationLevel()If positive, we spend some effort on each core: - At level 1, we use a simple heuristic to try to minimize an UNSAT core. - At level 2, we use propagation to minimize the core but also identify literal in at most one relationship in this core.
optional int32 core_minimization_level = 50 [default = 2];- Specified by:
getCoreMinimizationLevelin interfaceSatParametersOrBuilder- Returns:
- The coreMinimizationLevel.
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setCoreMinimizationLevel
If positive, we spend some effort on each core: - At level 1, we use a simple heuristic to try to minimize an UNSAT core. - At level 2, we use propagation to minimize the core but also identify literal in at most one relationship in this core.
optional int32 core_minimization_level = 50 [default = 2];- Parameters:
value- The coreMinimizationLevel to set.- Returns:
- This builder for chaining.
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clearCoreMinimizationLevel
If positive, we spend some effort on each core: - At level 1, we use a simple heuristic to try to minimize an UNSAT core. - At level 2, we use propagation to minimize the core but also identify literal in at most one relationship in this core.
optional int32 core_minimization_level = 50 [default = 2];- Returns:
- This builder for chaining.
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hasFindMultipleCores
public boolean hasFindMultipleCores()Whether we try to find more independent cores for a given set of assumptions in the core based max-SAT algorithms.
optional bool find_multiple_cores = 84 [default = true];- Specified by:
hasFindMultipleCoresin interfaceSatParametersOrBuilder- Returns:
- Whether the findMultipleCores field is set.
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getFindMultipleCores
public boolean getFindMultipleCores()Whether we try to find more independent cores for a given set of assumptions in the core based max-SAT algorithms.
optional bool find_multiple_cores = 84 [default = true];- Specified by:
getFindMultipleCoresin interfaceSatParametersOrBuilder- Returns:
- The findMultipleCores.
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setFindMultipleCores
Whether we try to find more independent cores for a given set of assumptions in the core based max-SAT algorithms.
optional bool find_multiple_cores = 84 [default = true];- Parameters:
value- The findMultipleCores to set.- Returns:
- This builder for chaining.
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clearFindMultipleCores
Whether we try to find more independent cores for a given set of assumptions in the core based max-SAT algorithms.
optional bool find_multiple_cores = 84 [default = true];- Returns:
- This builder for chaining.
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hasCoverOptimization
public boolean hasCoverOptimization()If true, when the max-sat algo find a core, we compute the minimal number of literals in the core that needs to be true to have a feasible solution. This is also called core exhaustion in more recent max-SAT papers.
optional bool cover_optimization = 89 [default = true];- Specified by:
hasCoverOptimizationin interfaceSatParametersOrBuilder- Returns:
- Whether the coverOptimization field is set.
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getCoverOptimization
public boolean getCoverOptimization()If true, when the max-sat algo find a core, we compute the minimal number of literals in the core that needs to be true to have a feasible solution. This is also called core exhaustion in more recent max-SAT papers.
optional bool cover_optimization = 89 [default = true];- Specified by:
getCoverOptimizationin interfaceSatParametersOrBuilder- Returns:
- The coverOptimization.
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setCoverOptimization
If true, when the max-sat algo find a core, we compute the minimal number of literals in the core that needs to be true to have a feasible solution. This is also called core exhaustion in more recent max-SAT papers.
optional bool cover_optimization = 89 [default = true];- Parameters:
value- The coverOptimization to set.- Returns:
- This builder for chaining.
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clearCoverOptimization
If true, when the max-sat algo find a core, we compute the minimal number of literals in the core that needs to be true to have a feasible solution. This is also called core exhaustion in more recent max-SAT papers.
optional bool cover_optimization = 89 [default = true];- Returns:
- This builder for chaining.
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hasMaxSatAssumptionOrder
public boolean hasMaxSatAssumptionOrder()optional .operations_research.sat.SatParameters.MaxSatAssumptionOrder max_sat_assumption_order = 51 [default = DEFAULT_ASSUMPTION_ORDER];- Specified by:
hasMaxSatAssumptionOrderin interfaceSatParametersOrBuilder- Returns:
- Whether the maxSatAssumptionOrder field is set.
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getMaxSatAssumptionOrder
optional .operations_research.sat.SatParameters.MaxSatAssumptionOrder max_sat_assumption_order = 51 [default = DEFAULT_ASSUMPTION_ORDER];- Specified by:
getMaxSatAssumptionOrderin interfaceSatParametersOrBuilder- Returns:
- The maxSatAssumptionOrder.
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setMaxSatAssumptionOrder
optional .operations_research.sat.SatParameters.MaxSatAssumptionOrder max_sat_assumption_order = 51 [default = DEFAULT_ASSUMPTION_ORDER];- Parameters:
value- The maxSatAssumptionOrder to set.- Returns:
- This builder for chaining.
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clearMaxSatAssumptionOrder
optional .operations_research.sat.SatParameters.MaxSatAssumptionOrder max_sat_assumption_order = 51 [default = DEFAULT_ASSUMPTION_ORDER];- Returns:
- This builder for chaining.
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hasMaxSatReverseAssumptionOrder
public boolean hasMaxSatReverseAssumptionOrder()If true, adds the assumption in the reverse order of the one defined by max_sat_assumption_order.
optional bool max_sat_reverse_assumption_order = 52 [default = false];- Specified by:
hasMaxSatReverseAssumptionOrderin interfaceSatParametersOrBuilder- Returns:
- Whether the maxSatReverseAssumptionOrder field is set.
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getMaxSatReverseAssumptionOrder
public boolean getMaxSatReverseAssumptionOrder()If true, adds the assumption in the reverse order of the one defined by max_sat_assumption_order.
optional bool max_sat_reverse_assumption_order = 52 [default = false];- Specified by:
getMaxSatReverseAssumptionOrderin interfaceSatParametersOrBuilder- Returns:
- The maxSatReverseAssumptionOrder.
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setMaxSatReverseAssumptionOrder
If true, adds the assumption in the reverse order of the one defined by max_sat_assumption_order.
optional bool max_sat_reverse_assumption_order = 52 [default = false];- Parameters:
value- The maxSatReverseAssumptionOrder to set.- Returns:
- This builder for chaining.
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clearMaxSatReverseAssumptionOrder
If true, adds the assumption in the reverse order of the one defined by max_sat_assumption_order.
optional bool max_sat_reverse_assumption_order = 52 [default = false];- Returns:
- This builder for chaining.
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hasMaxSatStratification
public boolean hasMaxSatStratification()optional .operations_research.sat.SatParameters.MaxSatStratificationAlgorithm max_sat_stratification = 53 [default = STRATIFICATION_DESCENT];- Specified by:
hasMaxSatStratificationin interfaceSatParametersOrBuilder- Returns:
- Whether the maxSatStratification field is set.
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getMaxSatStratification
optional .operations_research.sat.SatParameters.MaxSatStratificationAlgorithm max_sat_stratification = 53 [default = STRATIFICATION_DESCENT];- Specified by:
getMaxSatStratificationin interfaceSatParametersOrBuilder- Returns:
- The maxSatStratification.
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setMaxSatStratification
public SatParameters.Builder setMaxSatStratification(SatParameters.MaxSatStratificationAlgorithm value) optional .operations_research.sat.SatParameters.MaxSatStratificationAlgorithm max_sat_stratification = 53 [default = STRATIFICATION_DESCENT];- Parameters:
value- The maxSatStratification to set.- Returns:
- This builder for chaining.
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clearMaxSatStratification
optional .operations_research.sat.SatParameters.MaxSatStratificationAlgorithm max_sat_stratification = 53 [default = STRATIFICATION_DESCENT];- Returns:
- This builder for chaining.
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hasPropagationLoopDetectionFactor
public boolean hasPropagationLoopDetectionFactor()Some search decisions might cause a really large number of propagations to happen when integer variables with large domains are only reduced by 1 at each step. If we propagate more than the number of variable times this parameters we try to take counter-measure. Setting this to 0.0 disable this feature. TODO(user): Setting this to something like 10 helps in most cases, but the code is currently buggy and can cause the solve to enter a bad state where no progress is made.
optional double propagation_loop_detection_factor = 221 [default = 10];- Specified by:
hasPropagationLoopDetectionFactorin interfaceSatParametersOrBuilder- Returns:
- Whether the propagationLoopDetectionFactor field is set.
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getPropagationLoopDetectionFactor
public double getPropagationLoopDetectionFactor()Some search decisions might cause a really large number of propagations to happen when integer variables with large domains are only reduced by 1 at each step. If we propagate more than the number of variable times this parameters we try to take counter-measure. Setting this to 0.0 disable this feature. TODO(user): Setting this to something like 10 helps in most cases, but the code is currently buggy and can cause the solve to enter a bad state where no progress is made.
optional double propagation_loop_detection_factor = 221 [default = 10];- Specified by:
getPropagationLoopDetectionFactorin interfaceSatParametersOrBuilder- Returns:
- The propagationLoopDetectionFactor.
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setPropagationLoopDetectionFactor
Some search decisions might cause a really large number of propagations to happen when integer variables with large domains are only reduced by 1 at each step. If we propagate more than the number of variable times this parameters we try to take counter-measure. Setting this to 0.0 disable this feature. TODO(user): Setting this to something like 10 helps in most cases, but the code is currently buggy and can cause the solve to enter a bad state where no progress is made.
optional double propagation_loop_detection_factor = 221 [default = 10];- Parameters:
value- The propagationLoopDetectionFactor to set.- Returns:
- This builder for chaining.
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clearPropagationLoopDetectionFactor
Some search decisions might cause a really large number of propagations to happen when integer variables with large domains are only reduced by 1 at each step. If we propagate more than the number of variable times this parameters we try to take counter-measure. Setting this to 0.0 disable this feature. TODO(user): Setting this to something like 10 helps in most cases, but the code is currently buggy and can cause the solve to enter a bad state where no progress is made.
optional double propagation_loop_detection_factor = 221 [default = 10];- Returns:
- This builder for chaining.
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hasUsePrecedencesInDisjunctiveConstraint
public boolean hasUsePrecedencesInDisjunctiveConstraint()When this is true, then a disjunctive constraint will try to use the precedence relations between time intervals to propagate their bounds further. For instance if task A and B are both before C and task A and B are in disjunction, then we can deduce that task C must start after duration(A) + duration(B) instead of simply max(duration(A), duration(B)), provided that the start time for all task was currently zero. This always result in better propagation, but it is usually slow, so depending on the problem, turning this off may lead to a faster solution.
optional bool use_precedences_in_disjunctive_constraint = 74 [default = true];- Specified by:
hasUsePrecedencesInDisjunctiveConstraintin interfaceSatParametersOrBuilder- Returns:
- Whether the usePrecedencesInDisjunctiveConstraint field is set.
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getUsePrecedencesInDisjunctiveConstraint
public boolean getUsePrecedencesInDisjunctiveConstraint()When this is true, then a disjunctive constraint will try to use the precedence relations between time intervals to propagate their bounds further. For instance if task A and B are both before C and task A and B are in disjunction, then we can deduce that task C must start after duration(A) + duration(B) instead of simply max(duration(A), duration(B)), provided that the start time for all task was currently zero. This always result in better propagation, but it is usually slow, so depending on the problem, turning this off may lead to a faster solution.
optional bool use_precedences_in_disjunctive_constraint = 74 [default = true];- Specified by:
getUsePrecedencesInDisjunctiveConstraintin interfaceSatParametersOrBuilder- Returns:
- The usePrecedencesInDisjunctiveConstraint.
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setUsePrecedencesInDisjunctiveConstraint
When this is true, then a disjunctive constraint will try to use the precedence relations between time intervals to propagate their bounds further. For instance if task A and B are both before C and task A and B are in disjunction, then we can deduce that task C must start after duration(A) + duration(B) instead of simply max(duration(A), duration(B)), provided that the start time for all task was currently zero. This always result in better propagation, but it is usually slow, so depending on the problem, turning this off may lead to a faster solution.
optional bool use_precedences_in_disjunctive_constraint = 74 [default = true];- Parameters:
value- The usePrecedencesInDisjunctiveConstraint to set.- Returns:
- This builder for chaining.
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clearUsePrecedencesInDisjunctiveConstraint
When this is true, then a disjunctive constraint will try to use the precedence relations between time intervals to propagate their bounds further. For instance if task A and B are both before C and task A and B are in disjunction, then we can deduce that task C must start after duration(A) + duration(B) instead of simply max(duration(A), duration(B)), provided that the start time for all task was currently zero. This always result in better propagation, but it is usually slow, so depending on the problem, turning this off may lead to a faster solution.
optional bool use_precedences_in_disjunctive_constraint = 74 [default = true];- Returns:
- This builder for chaining.
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hasTransitivePrecedencesWorkLimit
public boolean hasTransitivePrecedencesWorkLimit()At root level, we might compute the transitive closure of "precedences" relations so that we can exploit that in scheduling problems. Setting this to zero disable the feature.
optional int32 transitive_precedences_work_limit = 327 [default = 1000000];- Specified by:
hasTransitivePrecedencesWorkLimitin interfaceSatParametersOrBuilder- Returns:
- Whether the transitivePrecedencesWorkLimit field is set.
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getTransitivePrecedencesWorkLimit
public int getTransitivePrecedencesWorkLimit()At root level, we might compute the transitive closure of "precedences" relations so that we can exploit that in scheduling problems. Setting this to zero disable the feature.
optional int32 transitive_precedences_work_limit = 327 [default = 1000000];- Specified by:
getTransitivePrecedencesWorkLimitin interfaceSatParametersOrBuilder- Returns:
- The transitivePrecedencesWorkLimit.
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setTransitivePrecedencesWorkLimit
At root level, we might compute the transitive closure of "precedences" relations so that we can exploit that in scheduling problems. Setting this to zero disable the feature.
optional int32 transitive_precedences_work_limit = 327 [default = 1000000];- Parameters:
value- The transitivePrecedencesWorkLimit to set.- Returns:
- This builder for chaining.
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clearTransitivePrecedencesWorkLimit
At root level, we might compute the transitive closure of "precedences" relations so that we can exploit that in scheduling problems. Setting this to zero disable the feature.
optional int32 transitive_precedences_work_limit = 327 [default = 1000000];- Returns:
- This builder for chaining.
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hasMaxSizeToCreatePrecedenceLiteralsInDisjunctive
public boolean hasMaxSizeToCreatePrecedenceLiteralsInDisjunctive()Create one literal for each disjunction of two pairs of tasks. This slows down the solve time, but improves the lower bound of the objective in the makespan case. This will be triggered if the number of intervals is less or equal than the parameter and if use_strong_propagation_in_disjunctive is true.
optional int32 max_size_to_create_precedence_literals_in_disjunctive = 229 [default = 60];- Specified by:
hasMaxSizeToCreatePrecedenceLiteralsInDisjunctivein interfaceSatParametersOrBuilder- Returns:
- Whether the maxSizeToCreatePrecedenceLiteralsInDisjunctive field is set.
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getMaxSizeToCreatePrecedenceLiteralsInDisjunctive
public int getMaxSizeToCreatePrecedenceLiteralsInDisjunctive()Create one literal for each disjunction of two pairs of tasks. This slows down the solve time, but improves the lower bound of the objective in the makespan case. This will be triggered if the number of intervals is less or equal than the parameter and if use_strong_propagation_in_disjunctive is true.
optional int32 max_size_to_create_precedence_literals_in_disjunctive = 229 [default = 60];- Specified by:
getMaxSizeToCreatePrecedenceLiteralsInDisjunctivein interfaceSatParametersOrBuilder- Returns:
- The maxSizeToCreatePrecedenceLiteralsInDisjunctive.
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setMaxSizeToCreatePrecedenceLiteralsInDisjunctive
Create one literal for each disjunction of two pairs of tasks. This slows down the solve time, but improves the lower bound of the objective in the makespan case. This will be triggered if the number of intervals is less or equal than the parameter and if use_strong_propagation_in_disjunctive is true.
optional int32 max_size_to_create_precedence_literals_in_disjunctive = 229 [default = 60];- Parameters:
value- The maxSizeToCreatePrecedenceLiteralsInDisjunctive to set.- Returns:
- This builder for chaining.
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clearMaxSizeToCreatePrecedenceLiteralsInDisjunctive
Create one literal for each disjunction of two pairs of tasks. This slows down the solve time, but improves the lower bound of the objective in the makespan case. This will be triggered if the number of intervals is less or equal than the parameter and if use_strong_propagation_in_disjunctive is true.
optional int32 max_size_to_create_precedence_literals_in_disjunctive = 229 [default = 60];- Returns:
- This builder for chaining.
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hasUseStrongPropagationInDisjunctive
public boolean hasUseStrongPropagationInDisjunctive()Enable stronger and more expensive propagation on no_overlap constraint.
optional bool use_strong_propagation_in_disjunctive = 230 [default = false];- Specified by:
hasUseStrongPropagationInDisjunctivein interfaceSatParametersOrBuilder- Returns:
- Whether the useStrongPropagationInDisjunctive field is set.
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getUseStrongPropagationInDisjunctive
public boolean getUseStrongPropagationInDisjunctive()Enable stronger and more expensive propagation on no_overlap constraint.
optional bool use_strong_propagation_in_disjunctive = 230 [default = false];- Specified by:
getUseStrongPropagationInDisjunctivein interfaceSatParametersOrBuilder- Returns:
- The useStrongPropagationInDisjunctive.
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setUseStrongPropagationInDisjunctive
Enable stronger and more expensive propagation on no_overlap constraint.
optional bool use_strong_propagation_in_disjunctive = 230 [default = false];- Parameters:
value- The useStrongPropagationInDisjunctive to set.- Returns:
- This builder for chaining.
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clearUseStrongPropagationInDisjunctive
Enable stronger and more expensive propagation on no_overlap constraint.
optional bool use_strong_propagation_in_disjunctive = 230 [default = false];- Returns:
- This builder for chaining.
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hasUseDynamicPrecedenceInDisjunctive
public boolean hasUseDynamicPrecedenceInDisjunctive()Whether we try to branch on decision "interval A before interval B" rather than on intervals bounds. This usually works better, but slow down a bit the time to find the first solution. These parameters are still EXPERIMENTAL, the result should be correct, but it some corner cases, they can cause some failing CHECK in the solver.
optional bool use_dynamic_precedence_in_disjunctive = 263 [default = false];- Specified by:
hasUseDynamicPrecedenceInDisjunctivein interfaceSatParametersOrBuilder- Returns:
- Whether the useDynamicPrecedenceInDisjunctive field is set.
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getUseDynamicPrecedenceInDisjunctive
public boolean getUseDynamicPrecedenceInDisjunctive()Whether we try to branch on decision "interval A before interval B" rather than on intervals bounds. This usually works better, but slow down a bit the time to find the first solution. These parameters are still EXPERIMENTAL, the result should be correct, but it some corner cases, they can cause some failing CHECK in the solver.
optional bool use_dynamic_precedence_in_disjunctive = 263 [default = false];- Specified by:
getUseDynamicPrecedenceInDisjunctivein interfaceSatParametersOrBuilder- Returns:
- The useDynamicPrecedenceInDisjunctive.
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setUseDynamicPrecedenceInDisjunctive
Whether we try to branch on decision "interval A before interval B" rather than on intervals bounds. This usually works better, but slow down a bit the time to find the first solution. These parameters are still EXPERIMENTAL, the result should be correct, but it some corner cases, they can cause some failing CHECK in the solver.
optional bool use_dynamic_precedence_in_disjunctive = 263 [default = false];- Parameters:
value- The useDynamicPrecedenceInDisjunctive to set.- Returns:
- This builder for chaining.
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clearUseDynamicPrecedenceInDisjunctive
Whether we try to branch on decision "interval A before interval B" rather than on intervals bounds. This usually works better, but slow down a bit the time to find the first solution. These parameters are still EXPERIMENTAL, the result should be correct, but it some corner cases, they can cause some failing CHECK in the solver.
optional bool use_dynamic_precedence_in_disjunctive = 263 [default = false];- Returns:
- This builder for chaining.
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hasUseDynamicPrecedenceInCumulative
public boolean hasUseDynamicPrecedenceInCumulative()optional bool use_dynamic_precedence_in_cumulative = 268 [default = false];- Specified by:
hasUseDynamicPrecedenceInCumulativein interfaceSatParametersOrBuilder- Returns:
- Whether the useDynamicPrecedenceInCumulative field is set.
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getUseDynamicPrecedenceInCumulative
public boolean getUseDynamicPrecedenceInCumulative()optional bool use_dynamic_precedence_in_cumulative = 268 [default = false];- Specified by:
getUseDynamicPrecedenceInCumulativein interfaceSatParametersOrBuilder- Returns:
- The useDynamicPrecedenceInCumulative.
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setUseDynamicPrecedenceInCumulative
optional bool use_dynamic_precedence_in_cumulative = 268 [default = false];- Parameters:
value- The useDynamicPrecedenceInCumulative to set.- Returns:
- This builder for chaining.
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clearUseDynamicPrecedenceInCumulative
optional bool use_dynamic_precedence_in_cumulative = 268 [default = false];- Returns:
- This builder for chaining.
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hasUseOverloadCheckerInCumulative
public boolean hasUseOverloadCheckerInCumulative()When this is true, the cumulative constraint is reinforced with overload checking, i.e., an additional level of reasoning based on energy. This additional level supplements the default level of reasoning as well as timetable edge finding. This always result in better propagation, but it is usually slow, so depending on the problem, turning this off may lead to a faster solution.
optional bool use_overload_checker_in_cumulative = 78 [default = false];- Specified by:
hasUseOverloadCheckerInCumulativein interfaceSatParametersOrBuilder- Returns:
- Whether the useOverloadCheckerInCumulative field is set.
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getUseOverloadCheckerInCumulative
public boolean getUseOverloadCheckerInCumulative()When this is true, the cumulative constraint is reinforced with overload checking, i.e., an additional level of reasoning based on energy. This additional level supplements the default level of reasoning as well as timetable edge finding. This always result in better propagation, but it is usually slow, so depending on the problem, turning this off may lead to a faster solution.
optional bool use_overload_checker_in_cumulative = 78 [default = false];- Specified by:
getUseOverloadCheckerInCumulativein interfaceSatParametersOrBuilder- Returns:
- The useOverloadCheckerInCumulative.
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setUseOverloadCheckerInCumulative
When this is true, the cumulative constraint is reinforced with overload checking, i.e., an additional level of reasoning based on energy. This additional level supplements the default level of reasoning as well as timetable edge finding. This always result in better propagation, but it is usually slow, so depending on the problem, turning this off may lead to a faster solution.
optional bool use_overload_checker_in_cumulative = 78 [default = false];- Parameters:
value- The useOverloadCheckerInCumulative to set.- Returns:
- This builder for chaining.
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clearUseOverloadCheckerInCumulative
When this is true, the cumulative constraint is reinforced with overload checking, i.e., an additional level of reasoning based on energy. This additional level supplements the default level of reasoning as well as timetable edge finding. This always result in better propagation, but it is usually slow, so depending on the problem, turning this off may lead to a faster solution.
optional bool use_overload_checker_in_cumulative = 78 [default = false];- Returns:
- This builder for chaining.
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hasUseConservativeScaleOverloadChecker
public boolean hasUseConservativeScaleOverloadChecker()Enable a heuristic to solve cumulative constraints using a modified energy constraint. We modify the usual energy definition by applying a super-additive function (also called "conservative scale" or "dual-feasible function") to the demand and the durations of the tasks. This heuristic is fast but for most problems it does not help much to find a solution.
optional bool use_conservative_scale_overload_checker = 286 [default = false];- Specified by:
hasUseConservativeScaleOverloadCheckerin interfaceSatParametersOrBuilder- Returns:
- Whether the useConservativeScaleOverloadChecker field is set.
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getUseConservativeScaleOverloadChecker
public boolean getUseConservativeScaleOverloadChecker()Enable a heuristic to solve cumulative constraints using a modified energy constraint. We modify the usual energy definition by applying a super-additive function (also called "conservative scale" or "dual-feasible function") to the demand and the durations of the tasks. This heuristic is fast but for most problems it does not help much to find a solution.
optional bool use_conservative_scale_overload_checker = 286 [default = false];- Specified by:
getUseConservativeScaleOverloadCheckerin interfaceSatParametersOrBuilder- Returns:
- The useConservativeScaleOverloadChecker.
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setUseConservativeScaleOverloadChecker
Enable a heuristic to solve cumulative constraints using a modified energy constraint. We modify the usual energy definition by applying a super-additive function (also called "conservative scale" or "dual-feasible function") to the demand and the durations of the tasks. This heuristic is fast but for most problems it does not help much to find a solution.
optional bool use_conservative_scale_overload_checker = 286 [default = false];- Parameters:
value- The useConservativeScaleOverloadChecker to set.- Returns:
- This builder for chaining.
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clearUseConservativeScaleOverloadChecker
Enable a heuristic to solve cumulative constraints using a modified energy constraint. We modify the usual energy definition by applying a super-additive function (also called "conservative scale" or "dual-feasible function") to the demand and the durations of the tasks. This heuristic is fast but for most problems it does not help much to find a solution.
optional bool use_conservative_scale_overload_checker = 286 [default = false];- Returns:
- This builder for chaining.
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hasUseTimetableEdgeFindingInCumulative
public boolean hasUseTimetableEdgeFindingInCumulative()When this is true, the cumulative constraint is reinforced with timetable edge finding, i.e., an additional level of reasoning based on the conjunction of energy and mandatory parts. This additional level supplements the default level of reasoning as well as overload_checker. This always result in better propagation, but it is usually slow, so depending on the problem, turning this off may lead to a faster solution.
optional bool use_timetable_edge_finding_in_cumulative = 79 [default = false];- Specified by:
hasUseTimetableEdgeFindingInCumulativein interfaceSatParametersOrBuilder- Returns:
- Whether the useTimetableEdgeFindingInCumulative field is set.
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getUseTimetableEdgeFindingInCumulative
public boolean getUseTimetableEdgeFindingInCumulative()When this is true, the cumulative constraint is reinforced with timetable edge finding, i.e., an additional level of reasoning based on the conjunction of energy and mandatory parts. This additional level supplements the default level of reasoning as well as overload_checker. This always result in better propagation, but it is usually slow, so depending on the problem, turning this off may lead to a faster solution.
optional bool use_timetable_edge_finding_in_cumulative = 79 [default = false];- Specified by:
getUseTimetableEdgeFindingInCumulativein interfaceSatParametersOrBuilder- Returns:
- The useTimetableEdgeFindingInCumulative.
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setUseTimetableEdgeFindingInCumulative
When this is true, the cumulative constraint is reinforced with timetable edge finding, i.e., an additional level of reasoning based on the conjunction of energy and mandatory parts. This additional level supplements the default level of reasoning as well as overload_checker. This always result in better propagation, but it is usually slow, so depending on the problem, turning this off may lead to a faster solution.
optional bool use_timetable_edge_finding_in_cumulative = 79 [default = false];- Parameters:
value- The useTimetableEdgeFindingInCumulative to set.- Returns:
- This builder for chaining.
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clearUseTimetableEdgeFindingInCumulative
When this is true, the cumulative constraint is reinforced with timetable edge finding, i.e., an additional level of reasoning based on the conjunction of energy and mandatory parts. This additional level supplements the default level of reasoning as well as overload_checker. This always result in better propagation, but it is usually slow, so depending on the problem, turning this off may lead to a faster solution.
optional bool use_timetable_edge_finding_in_cumulative = 79 [default = false];- Returns:
- This builder for chaining.
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hasMaxNumIntervalsForTimetableEdgeFinding
public boolean hasMaxNumIntervalsForTimetableEdgeFinding()Max number of intervals for the timetable_edge_finding algorithm to propagate. A value of 0 disables the constraint.
optional int32 max_num_intervals_for_timetable_edge_finding = 260 [default = 100];- Specified by:
hasMaxNumIntervalsForTimetableEdgeFindingin interfaceSatParametersOrBuilder- Returns:
- Whether the maxNumIntervalsForTimetableEdgeFinding field is set.
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getMaxNumIntervalsForTimetableEdgeFinding
public int getMaxNumIntervalsForTimetableEdgeFinding()Max number of intervals for the timetable_edge_finding algorithm to propagate. A value of 0 disables the constraint.
optional int32 max_num_intervals_for_timetable_edge_finding = 260 [default = 100];- Specified by:
getMaxNumIntervalsForTimetableEdgeFindingin interfaceSatParametersOrBuilder- Returns:
- The maxNumIntervalsForTimetableEdgeFinding.
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setMaxNumIntervalsForTimetableEdgeFinding
Max number of intervals for the timetable_edge_finding algorithm to propagate. A value of 0 disables the constraint.
optional int32 max_num_intervals_for_timetable_edge_finding = 260 [default = 100];- Parameters:
value- The maxNumIntervalsForTimetableEdgeFinding to set.- Returns:
- This builder for chaining.
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clearMaxNumIntervalsForTimetableEdgeFinding
Max number of intervals for the timetable_edge_finding algorithm to propagate. A value of 0 disables the constraint.
optional int32 max_num_intervals_for_timetable_edge_finding = 260 [default = 100];- Returns:
- This builder for chaining.
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hasUseHardPrecedencesInCumulative
public boolean hasUseHardPrecedencesInCumulative()If true, detect and create constraint for integer variable that are "after" a set of intervals in the same cumulative constraint. Experimental: by default we just use "direct" precedences. If exploit_all_precedences is true, we explore the full precedence graph. This assumes we have a DAG otherwise it fails.
optional bool use_hard_precedences_in_cumulative = 215 [default = false];- Specified by:
hasUseHardPrecedencesInCumulativein interfaceSatParametersOrBuilder- Returns:
- Whether the useHardPrecedencesInCumulative field is set.
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getUseHardPrecedencesInCumulative
public boolean getUseHardPrecedencesInCumulative()If true, detect and create constraint for integer variable that are "after" a set of intervals in the same cumulative constraint. Experimental: by default we just use "direct" precedences. If exploit_all_precedences is true, we explore the full precedence graph. This assumes we have a DAG otherwise it fails.
optional bool use_hard_precedences_in_cumulative = 215 [default = false];- Specified by:
getUseHardPrecedencesInCumulativein interfaceSatParametersOrBuilder- Returns:
- The useHardPrecedencesInCumulative.
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setUseHardPrecedencesInCumulative
If true, detect and create constraint for integer variable that are "after" a set of intervals in the same cumulative constraint. Experimental: by default we just use "direct" precedences. If exploit_all_precedences is true, we explore the full precedence graph. This assumes we have a DAG otherwise it fails.
optional bool use_hard_precedences_in_cumulative = 215 [default = false];- Parameters:
value- The useHardPrecedencesInCumulative to set.- Returns:
- This builder for chaining.
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clearUseHardPrecedencesInCumulative
If true, detect and create constraint for integer variable that are "after" a set of intervals in the same cumulative constraint. Experimental: by default we just use "direct" precedences. If exploit_all_precedences is true, we explore the full precedence graph. This assumes we have a DAG otherwise it fails.
optional bool use_hard_precedences_in_cumulative = 215 [default = false];- Returns:
- This builder for chaining.
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hasExploitAllPrecedences
public boolean hasExploitAllPrecedences()optional bool exploit_all_precedences = 220 [default = false];- Specified by:
hasExploitAllPrecedencesin interfaceSatParametersOrBuilder- Returns:
- Whether the exploitAllPrecedences field is set.
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getExploitAllPrecedences
public boolean getExploitAllPrecedences()optional bool exploit_all_precedences = 220 [default = false];- Specified by:
getExploitAllPrecedencesin interfaceSatParametersOrBuilder- Returns:
- The exploitAllPrecedences.
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setExploitAllPrecedences
optional bool exploit_all_precedences = 220 [default = false];- Parameters:
value- The exploitAllPrecedences to set.- Returns:
- This builder for chaining.
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clearExploitAllPrecedences
optional bool exploit_all_precedences = 220 [default = false];- Returns:
- This builder for chaining.
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hasUseDisjunctiveConstraintInCumulative
public boolean hasUseDisjunctiveConstraintInCumulative()When this is true, the cumulative constraint is reinforced with propagators from the disjunctive constraint to improve the inference on a set of tasks that are disjunctive at the root of the problem. This additional level supplements the default level of reasoning. Propagators of the cumulative constraint will not be used at all if all the tasks are disjunctive at root node. This always result in better propagation, but it is usually slow, so depending on the problem, turning this off may lead to a faster solution.
optional bool use_disjunctive_constraint_in_cumulative = 80 [default = true];- Specified by:
hasUseDisjunctiveConstraintInCumulativein interfaceSatParametersOrBuilder- Returns:
- Whether the useDisjunctiveConstraintInCumulative field is set.
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getUseDisjunctiveConstraintInCumulative
public boolean getUseDisjunctiveConstraintInCumulative()When this is true, the cumulative constraint is reinforced with propagators from the disjunctive constraint to improve the inference on a set of tasks that are disjunctive at the root of the problem. This additional level supplements the default level of reasoning. Propagators of the cumulative constraint will not be used at all if all the tasks are disjunctive at root node. This always result in better propagation, but it is usually slow, so depending on the problem, turning this off may lead to a faster solution.
optional bool use_disjunctive_constraint_in_cumulative = 80 [default = true];- Specified by:
getUseDisjunctiveConstraintInCumulativein interfaceSatParametersOrBuilder- Returns:
- The useDisjunctiveConstraintInCumulative.
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setUseDisjunctiveConstraintInCumulative
When this is true, the cumulative constraint is reinforced with propagators from the disjunctive constraint to improve the inference on a set of tasks that are disjunctive at the root of the problem. This additional level supplements the default level of reasoning. Propagators of the cumulative constraint will not be used at all if all the tasks are disjunctive at root node. This always result in better propagation, but it is usually slow, so depending on the problem, turning this off may lead to a faster solution.
optional bool use_disjunctive_constraint_in_cumulative = 80 [default = true];- Parameters:
value- The useDisjunctiveConstraintInCumulative to set.- Returns:
- This builder for chaining.
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clearUseDisjunctiveConstraintInCumulative
When this is true, the cumulative constraint is reinforced with propagators from the disjunctive constraint to improve the inference on a set of tasks that are disjunctive at the root of the problem. This additional level supplements the default level of reasoning. Propagators of the cumulative constraint will not be used at all if all the tasks are disjunctive at root node. This always result in better propagation, but it is usually slow, so depending on the problem, turning this off may lead to a faster solution.
optional bool use_disjunctive_constraint_in_cumulative = 80 [default = true];- Returns:
- This builder for chaining.
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hasNoOverlap2DBooleanRelationsLimit
public boolean hasNoOverlap2DBooleanRelationsLimit()If less than this number of boxes are present in a no-overlap 2d, we create 4 Booleans per pair of boxes: - Box 2 is after Box 1 on x. - Box 1 is after Box 2 on x. - Box 2 is after Box 1 on y. - Box 1 is after Box 2 on y. Note that at least one of them must be true, and at most one on x and one on y can be true. This can significantly help in closing small problem. The SAT reasoning can be a lot more powerful when we take decision on such positional relations.
optional int32 no_overlap_2d_boolean_relations_limit = 321 [default = 10];- Specified by:
hasNoOverlap2DBooleanRelationsLimitin interfaceSatParametersOrBuilder- Returns:
- Whether the noOverlap2dBooleanRelationsLimit field is set.
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getNoOverlap2DBooleanRelationsLimit
public int getNoOverlap2DBooleanRelationsLimit()If less than this number of boxes are present in a no-overlap 2d, we create 4 Booleans per pair of boxes: - Box 2 is after Box 1 on x. - Box 1 is after Box 2 on x. - Box 2 is after Box 1 on y. - Box 1 is after Box 2 on y. Note that at least one of them must be true, and at most one on x and one on y can be true. This can significantly help in closing small problem. The SAT reasoning can be a lot more powerful when we take decision on such positional relations.
optional int32 no_overlap_2d_boolean_relations_limit = 321 [default = 10];- Specified by:
getNoOverlap2DBooleanRelationsLimitin interfaceSatParametersOrBuilder- Returns:
- The noOverlap2dBooleanRelationsLimit.
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setNoOverlap2DBooleanRelationsLimit
If less than this number of boxes are present in a no-overlap 2d, we create 4 Booleans per pair of boxes: - Box 2 is after Box 1 on x. - Box 1 is after Box 2 on x. - Box 2 is after Box 1 on y. - Box 1 is after Box 2 on y. Note that at least one of them must be true, and at most one on x and one on y can be true. This can significantly help in closing small problem. The SAT reasoning can be a lot more powerful when we take decision on such positional relations.
optional int32 no_overlap_2d_boolean_relations_limit = 321 [default = 10];- Parameters:
value- The noOverlap2dBooleanRelationsLimit to set.- Returns:
- This builder for chaining.
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clearNoOverlap2DBooleanRelationsLimit
If less than this number of boxes are present in a no-overlap 2d, we create 4 Booleans per pair of boxes: - Box 2 is after Box 1 on x. - Box 1 is after Box 2 on x. - Box 2 is after Box 1 on y. - Box 1 is after Box 2 on y. Note that at least one of them must be true, and at most one on x and one on y can be true. This can significantly help in closing small problem. The SAT reasoning can be a lot more powerful when we take decision on such positional relations.
optional int32 no_overlap_2d_boolean_relations_limit = 321 [default = 10];- Returns:
- This builder for chaining.
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hasUseTimetablingInNoOverlap2D
public boolean hasUseTimetablingInNoOverlap2D()When this is true, the no_overlap_2d constraint is reinforced with propagators from the cumulative constraints. It consists of ignoring the position of rectangles in one position and projecting the no_overlap_2d on the other dimension to create a cumulative constraint. This is done on both axis. This additional level supplements the default level of reasoning.
optional bool use_timetabling_in_no_overlap_2d = 200 [default = false];- Specified by:
hasUseTimetablingInNoOverlap2Din interfaceSatParametersOrBuilder- Returns:
- Whether the useTimetablingInNoOverlap2d field is set.
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getUseTimetablingInNoOverlap2D
public boolean getUseTimetablingInNoOverlap2D()When this is true, the no_overlap_2d constraint is reinforced with propagators from the cumulative constraints. It consists of ignoring the position of rectangles in one position and projecting the no_overlap_2d on the other dimension to create a cumulative constraint. This is done on both axis. This additional level supplements the default level of reasoning.
optional bool use_timetabling_in_no_overlap_2d = 200 [default = false];- Specified by:
getUseTimetablingInNoOverlap2Din interfaceSatParametersOrBuilder- Returns:
- The useTimetablingInNoOverlap2d.
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setUseTimetablingInNoOverlap2D
When this is true, the no_overlap_2d constraint is reinforced with propagators from the cumulative constraints. It consists of ignoring the position of rectangles in one position and projecting the no_overlap_2d on the other dimension to create a cumulative constraint. This is done on both axis. This additional level supplements the default level of reasoning.
optional bool use_timetabling_in_no_overlap_2d = 200 [default = false];- Parameters:
value- The useTimetablingInNoOverlap2d to set.- Returns:
- This builder for chaining.
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clearUseTimetablingInNoOverlap2D
When this is true, the no_overlap_2d constraint is reinforced with propagators from the cumulative constraints. It consists of ignoring the position of rectangles in one position and projecting the no_overlap_2d on the other dimension to create a cumulative constraint. This is done on both axis. This additional level supplements the default level of reasoning.
optional bool use_timetabling_in_no_overlap_2d = 200 [default = false];- Returns:
- This builder for chaining.
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hasUseEnergeticReasoningInNoOverlap2D
public boolean hasUseEnergeticReasoningInNoOverlap2D()When this is true, the no_overlap_2d constraint is reinforced with energetic reasoning. This additional level supplements the default level of reasoning.
optional bool use_energetic_reasoning_in_no_overlap_2d = 213 [default = false];- Specified by:
hasUseEnergeticReasoningInNoOverlap2Din interfaceSatParametersOrBuilder- Returns:
- Whether the useEnergeticReasoningInNoOverlap2d field is set.
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getUseEnergeticReasoningInNoOverlap2D
public boolean getUseEnergeticReasoningInNoOverlap2D()When this is true, the no_overlap_2d constraint is reinforced with energetic reasoning. This additional level supplements the default level of reasoning.
optional bool use_energetic_reasoning_in_no_overlap_2d = 213 [default = false];- Specified by:
getUseEnergeticReasoningInNoOverlap2Din interfaceSatParametersOrBuilder- Returns:
- The useEnergeticReasoningInNoOverlap2d.
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setUseEnergeticReasoningInNoOverlap2D
When this is true, the no_overlap_2d constraint is reinforced with energetic reasoning. This additional level supplements the default level of reasoning.
optional bool use_energetic_reasoning_in_no_overlap_2d = 213 [default = false];- Parameters:
value- The useEnergeticReasoningInNoOverlap2d to set.- Returns:
- This builder for chaining.
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clearUseEnergeticReasoningInNoOverlap2D
When this is true, the no_overlap_2d constraint is reinforced with energetic reasoning. This additional level supplements the default level of reasoning.
optional bool use_energetic_reasoning_in_no_overlap_2d = 213 [default = false];- Returns:
- This builder for chaining.
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hasUseAreaEnergeticReasoningInNoOverlap2D
public boolean hasUseAreaEnergeticReasoningInNoOverlap2D()When this is true, the no_overlap_2d constraint is reinforced with an energetic reasoning that uses an area-based energy. This can be combined with the two other overlap heuristics above.
optional bool use_area_energetic_reasoning_in_no_overlap_2d = 271 [default = false];- Specified by:
hasUseAreaEnergeticReasoningInNoOverlap2Din interfaceSatParametersOrBuilder- Returns:
- Whether the useAreaEnergeticReasoningInNoOverlap2d field is set.
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getUseAreaEnergeticReasoningInNoOverlap2D
public boolean getUseAreaEnergeticReasoningInNoOverlap2D()When this is true, the no_overlap_2d constraint is reinforced with an energetic reasoning that uses an area-based energy. This can be combined with the two other overlap heuristics above.
optional bool use_area_energetic_reasoning_in_no_overlap_2d = 271 [default = false];- Specified by:
getUseAreaEnergeticReasoningInNoOverlap2Din interfaceSatParametersOrBuilder- Returns:
- The useAreaEnergeticReasoningInNoOverlap2d.
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setUseAreaEnergeticReasoningInNoOverlap2D
When this is true, the no_overlap_2d constraint is reinforced with an energetic reasoning that uses an area-based energy. This can be combined with the two other overlap heuristics above.
optional bool use_area_energetic_reasoning_in_no_overlap_2d = 271 [default = false];- Parameters:
value- The useAreaEnergeticReasoningInNoOverlap2d to set.- Returns:
- This builder for chaining.
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clearUseAreaEnergeticReasoningInNoOverlap2D
When this is true, the no_overlap_2d constraint is reinforced with an energetic reasoning that uses an area-based energy. This can be combined with the two other overlap heuristics above.
optional bool use_area_energetic_reasoning_in_no_overlap_2d = 271 [default = false];- Returns:
- This builder for chaining.
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hasUseTryEdgeReasoningInNoOverlap2D
public boolean hasUseTryEdgeReasoningInNoOverlap2D()optional bool use_try_edge_reasoning_in_no_overlap_2d = 299 [default = false];- Specified by:
hasUseTryEdgeReasoningInNoOverlap2Din interfaceSatParametersOrBuilder- Returns:
- Whether the useTryEdgeReasoningInNoOverlap2d field is set.
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getUseTryEdgeReasoningInNoOverlap2D
public boolean getUseTryEdgeReasoningInNoOverlap2D()optional bool use_try_edge_reasoning_in_no_overlap_2d = 299 [default = false];- Specified by:
getUseTryEdgeReasoningInNoOverlap2Din interfaceSatParametersOrBuilder- Returns:
- The useTryEdgeReasoningInNoOverlap2d.
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setUseTryEdgeReasoningInNoOverlap2D
optional bool use_try_edge_reasoning_in_no_overlap_2d = 299 [default = false];- Parameters:
value- The useTryEdgeReasoningInNoOverlap2d to set.- Returns:
- This builder for chaining.
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clearUseTryEdgeReasoningInNoOverlap2D
optional bool use_try_edge_reasoning_in_no_overlap_2d = 299 [default = false];- Returns:
- This builder for chaining.
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hasMaxPairsPairwiseReasoningInNoOverlap2D
public boolean hasMaxPairsPairwiseReasoningInNoOverlap2D()If the number of pairs to look is below this threshold, do an extra step of propagation in the no_overlap_2d constraint by looking at all pairs of intervals.
optional int32 max_pairs_pairwise_reasoning_in_no_overlap_2d = 276 [default = 1250];- Specified by:
hasMaxPairsPairwiseReasoningInNoOverlap2Din interfaceSatParametersOrBuilder- Returns:
- Whether the maxPairsPairwiseReasoningInNoOverlap2d field is set.
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getMaxPairsPairwiseReasoningInNoOverlap2D
public int getMaxPairsPairwiseReasoningInNoOverlap2D()If the number of pairs to look is below this threshold, do an extra step of propagation in the no_overlap_2d constraint by looking at all pairs of intervals.
optional int32 max_pairs_pairwise_reasoning_in_no_overlap_2d = 276 [default = 1250];- Specified by:
getMaxPairsPairwiseReasoningInNoOverlap2Din interfaceSatParametersOrBuilder- Returns:
- The maxPairsPairwiseReasoningInNoOverlap2d.
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setMaxPairsPairwiseReasoningInNoOverlap2D
If the number of pairs to look is below this threshold, do an extra step of propagation in the no_overlap_2d constraint by looking at all pairs of intervals.
optional int32 max_pairs_pairwise_reasoning_in_no_overlap_2d = 276 [default = 1250];- Parameters:
value- The maxPairsPairwiseReasoningInNoOverlap2d to set.- Returns:
- This builder for chaining.
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clearMaxPairsPairwiseReasoningInNoOverlap2D
If the number of pairs to look is below this threshold, do an extra step of propagation in the no_overlap_2d constraint by looking at all pairs of intervals.
optional int32 max_pairs_pairwise_reasoning_in_no_overlap_2d = 276 [default = 1250];- Returns:
- This builder for chaining.
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hasMaximumRegionsToSplitInDisconnectedNoOverlap2D
public boolean hasMaximumRegionsToSplitInDisconnectedNoOverlap2D()Detects when the space where items of a no_overlap_2d constraint can placed is disjoint (ie., fixed boxes split the domain). When it is the case, we can introduce a boolean for each pair <item, component> encoding whether the item is in the component or not. Then we replace the original no_overlap_2d constraint by one no_overlap_2d constraint for each component, with the new booleans as the enforcement_literal of the intervals. This is equivalent to expanding the original no_overlap_2d constraint into a bin packing problem with each connected component being a bin. This heuristic is only done when the number of regions to split is less than this parameter and <= 1 disables it.
optional int32 maximum_regions_to_split_in_disconnected_no_overlap_2d = 315 [default = 0];- Specified by:
hasMaximumRegionsToSplitInDisconnectedNoOverlap2Din interfaceSatParametersOrBuilder- Returns:
- Whether the maximumRegionsToSplitInDisconnectedNoOverlap2d field is set.
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getMaximumRegionsToSplitInDisconnectedNoOverlap2D
public int getMaximumRegionsToSplitInDisconnectedNoOverlap2D()Detects when the space where items of a no_overlap_2d constraint can placed is disjoint (ie., fixed boxes split the domain). When it is the case, we can introduce a boolean for each pair <item, component> encoding whether the item is in the component or not. Then we replace the original no_overlap_2d constraint by one no_overlap_2d constraint for each component, with the new booleans as the enforcement_literal of the intervals. This is equivalent to expanding the original no_overlap_2d constraint into a bin packing problem with each connected component being a bin. This heuristic is only done when the number of regions to split is less than this parameter and <= 1 disables it.
optional int32 maximum_regions_to_split_in_disconnected_no_overlap_2d = 315 [default = 0];- Specified by:
getMaximumRegionsToSplitInDisconnectedNoOverlap2Din interfaceSatParametersOrBuilder- Returns:
- The maximumRegionsToSplitInDisconnectedNoOverlap2d.
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setMaximumRegionsToSplitInDisconnectedNoOverlap2D
Detects when the space where items of a no_overlap_2d constraint can placed is disjoint (ie., fixed boxes split the domain). When it is the case, we can introduce a boolean for each pair <item, component> encoding whether the item is in the component or not. Then we replace the original no_overlap_2d constraint by one no_overlap_2d constraint for each component, with the new booleans as the enforcement_literal of the intervals. This is equivalent to expanding the original no_overlap_2d constraint into a bin packing problem with each connected component being a bin. This heuristic is only done when the number of regions to split is less than this parameter and <= 1 disables it.
optional int32 maximum_regions_to_split_in_disconnected_no_overlap_2d = 315 [default = 0];- Parameters:
value- The maximumRegionsToSplitInDisconnectedNoOverlap2d to set.- Returns:
- This builder for chaining.
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clearMaximumRegionsToSplitInDisconnectedNoOverlap2D
Detects when the space where items of a no_overlap_2d constraint can placed is disjoint (ie., fixed boxes split the domain). When it is the case, we can introduce a boolean for each pair <item, component> encoding whether the item is in the component or not. Then we replace the original no_overlap_2d constraint by one no_overlap_2d constraint for each component, with the new booleans as the enforcement_literal of the intervals. This is equivalent to expanding the original no_overlap_2d constraint into a bin packing problem with each connected component being a bin. This heuristic is only done when the number of regions to split is less than this parameter and <= 1 disables it.
optional int32 maximum_regions_to_split_in_disconnected_no_overlap_2d = 315 [default = 0];- Returns:
- This builder for chaining.
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hasUseLinear3ForNoOverlap2DPrecedences
public boolean hasUseLinear3ForNoOverlap2DPrecedences()When set, this activates a propagator for the no_overlap_2d constraint that uses any eventual linear constraints of the model in the form `{start interval 1} - {end interval 2} + c*w <= ub` to detect that two intervals must overlap in one dimension for some values of `w`. This is particularly useful for problems where the distance between two boxes is part of the model.optional bool use_linear3_for_no_overlap_2d_precedences = 323 [default = true];- Specified by:
hasUseLinear3ForNoOverlap2DPrecedencesin interfaceSatParametersOrBuilder- Returns:
- Whether the useLinear3ForNoOverlap2dPrecedences field is set.
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getUseLinear3ForNoOverlap2DPrecedences
public boolean getUseLinear3ForNoOverlap2DPrecedences()When set, this activates a propagator for the no_overlap_2d constraint that uses any eventual linear constraints of the model in the form `{start interval 1} - {end interval 2} + c*w <= ub` to detect that two intervals must overlap in one dimension for some values of `w`. This is particularly useful for problems where the distance between two boxes is part of the model.optional bool use_linear3_for_no_overlap_2d_precedences = 323 [default = true];- Specified by:
getUseLinear3ForNoOverlap2DPrecedencesin interfaceSatParametersOrBuilder- Returns:
- The useLinear3ForNoOverlap2dPrecedences.
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setUseLinear3ForNoOverlap2DPrecedences
When set, this activates a propagator for the no_overlap_2d constraint that uses any eventual linear constraints of the model in the form `{start interval 1} - {end interval 2} + c*w <= ub` to detect that two intervals must overlap in one dimension for some values of `w`. This is particularly useful for problems where the distance between two boxes is part of the model.optional bool use_linear3_for_no_overlap_2d_precedences = 323 [default = true];- Parameters:
value- The useLinear3ForNoOverlap2dPrecedences to set.- Returns:
- This builder for chaining.
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clearUseLinear3ForNoOverlap2DPrecedences
When set, this activates a propagator for the no_overlap_2d constraint that uses any eventual linear constraints of the model in the form `{start interval 1} - {end interval 2} + c*w <= ub` to detect that two intervals must overlap in one dimension for some values of `w`. This is particularly useful for problems where the distance between two boxes is part of the model.optional bool use_linear3_for_no_overlap_2d_precedences = 323 [default = true];- Returns:
- This builder for chaining.
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hasUseDualSchedulingHeuristics
public boolean hasUseDualSchedulingHeuristics()When set, it activates a few scheduling parameters to improve the lower bound of scheduling problems. This is only effective with multiple workers as it modifies the reduced_cost, lb_tree_search, and probing workers.
optional bool use_dual_scheduling_heuristics = 214 [default = true];- Specified by:
hasUseDualSchedulingHeuristicsin interfaceSatParametersOrBuilder- Returns:
- Whether the useDualSchedulingHeuristics field is set.
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getUseDualSchedulingHeuristics
public boolean getUseDualSchedulingHeuristics()When set, it activates a few scheduling parameters to improve the lower bound of scheduling problems. This is only effective with multiple workers as it modifies the reduced_cost, lb_tree_search, and probing workers.
optional bool use_dual_scheduling_heuristics = 214 [default = true];- Specified by:
getUseDualSchedulingHeuristicsin interfaceSatParametersOrBuilder- Returns:
- The useDualSchedulingHeuristics.
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setUseDualSchedulingHeuristics
When set, it activates a few scheduling parameters to improve the lower bound of scheduling problems. This is only effective with multiple workers as it modifies the reduced_cost, lb_tree_search, and probing workers.
optional bool use_dual_scheduling_heuristics = 214 [default = true];- Parameters:
value- The useDualSchedulingHeuristics to set.- Returns:
- This builder for chaining.
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clearUseDualSchedulingHeuristics
When set, it activates a few scheduling parameters to improve the lower bound of scheduling problems. This is only effective with multiple workers as it modifies the reduced_cost, lb_tree_search, and probing workers.
optional bool use_dual_scheduling_heuristics = 214 [default = true];- Returns:
- This builder for chaining.
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hasUseAllDifferentForCircuit
public boolean hasUseAllDifferentForCircuit()Turn on extra propagation for the circuit constraint. This can be quite slow.
optional bool use_all_different_for_circuit = 311 [default = false];- Specified by:
hasUseAllDifferentForCircuitin interfaceSatParametersOrBuilder- Returns:
- Whether the useAllDifferentForCircuit field is set.
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getUseAllDifferentForCircuit
public boolean getUseAllDifferentForCircuit()Turn on extra propagation for the circuit constraint. This can be quite slow.
optional bool use_all_different_for_circuit = 311 [default = false];- Specified by:
getUseAllDifferentForCircuitin interfaceSatParametersOrBuilder- Returns:
- The useAllDifferentForCircuit.
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setUseAllDifferentForCircuit
Turn on extra propagation for the circuit constraint. This can be quite slow.
optional bool use_all_different_for_circuit = 311 [default = false];- Parameters:
value- The useAllDifferentForCircuit to set.- Returns:
- This builder for chaining.
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clearUseAllDifferentForCircuit
Turn on extra propagation for the circuit constraint. This can be quite slow.
optional bool use_all_different_for_circuit = 311 [default = false];- Returns:
- This builder for chaining.
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hasRoutingCutSubsetSizeForBinaryRelationBound
public boolean hasRoutingCutSubsetSizeForBinaryRelationBound()If the size of a subset of nodes of a RoutesConstraint is less than this value, use linear constraints of size 1 and 2 (such as capacity and time window constraints) enforced by the arc literals to compute cuts for this subset (unless the subset size is less than routing_cut_subset_size_for_tight_binary_relation_bound, in which case the corresponding algorithm is used instead). The algorithm for these cuts has a O(n^3) complexity, where n is the subset size. Hence the value of this parameter should not be too large (e.g. 10 or 20).
optional int32 routing_cut_subset_size_for_binary_relation_bound = 312 [default = 0];- Specified by:
hasRoutingCutSubsetSizeForBinaryRelationBoundin interfaceSatParametersOrBuilder- Returns:
- Whether the routingCutSubsetSizeForBinaryRelationBound field is set.
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getRoutingCutSubsetSizeForBinaryRelationBound
public int getRoutingCutSubsetSizeForBinaryRelationBound()If the size of a subset of nodes of a RoutesConstraint is less than this value, use linear constraints of size 1 and 2 (such as capacity and time window constraints) enforced by the arc literals to compute cuts for this subset (unless the subset size is less than routing_cut_subset_size_for_tight_binary_relation_bound, in which case the corresponding algorithm is used instead). The algorithm for these cuts has a O(n^3) complexity, where n is the subset size. Hence the value of this parameter should not be too large (e.g. 10 or 20).
optional int32 routing_cut_subset_size_for_binary_relation_bound = 312 [default = 0];- Specified by:
getRoutingCutSubsetSizeForBinaryRelationBoundin interfaceSatParametersOrBuilder- Returns:
- The routingCutSubsetSizeForBinaryRelationBound.
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setRoutingCutSubsetSizeForBinaryRelationBound
If the size of a subset of nodes of a RoutesConstraint is less than this value, use linear constraints of size 1 and 2 (such as capacity and time window constraints) enforced by the arc literals to compute cuts for this subset (unless the subset size is less than routing_cut_subset_size_for_tight_binary_relation_bound, in which case the corresponding algorithm is used instead). The algorithm for these cuts has a O(n^3) complexity, where n is the subset size. Hence the value of this parameter should not be too large (e.g. 10 or 20).
optional int32 routing_cut_subset_size_for_binary_relation_bound = 312 [default = 0];- Parameters:
value- The routingCutSubsetSizeForBinaryRelationBound to set.- Returns:
- This builder for chaining.
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clearRoutingCutSubsetSizeForBinaryRelationBound
If the size of a subset of nodes of a RoutesConstraint is less than this value, use linear constraints of size 1 and 2 (such as capacity and time window constraints) enforced by the arc literals to compute cuts for this subset (unless the subset size is less than routing_cut_subset_size_for_tight_binary_relation_bound, in which case the corresponding algorithm is used instead). The algorithm for these cuts has a O(n^3) complexity, where n is the subset size. Hence the value of this parameter should not be too large (e.g. 10 or 20).
optional int32 routing_cut_subset_size_for_binary_relation_bound = 312 [default = 0];- Returns:
- This builder for chaining.
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hasRoutingCutSubsetSizeForTightBinaryRelationBound
public boolean hasRoutingCutSubsetSizeForTightBinaryRelationBound()Similar to above, but with a different algorithm producing better cuts, at the price of a higher O(2^n) complexity, where n is the subset size. Hence the value of this parameter should be small (e.g. less than 10).
optional int32 routing_cut_subset_size_for_tight_binary_relation_bound = 313 [default = 0];- Specified by:
hasRoutingCutSubsetSizeForTightBinaryRelationBoundin interfaceSatParametersOrBuilder- Returns:
- Whether the routingCutSubsetSizeForTightBinaryRelationBound field is set.
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getRoutingCutSubsetSizeForTightBinaryRelationBound
public int getRoutingCutSubsetSizeForTightBinaryRelationBound()Similar to above, but with a different algorithm producing better cuts, at the price of a higher O(2^n) complexity, where n is the subset size. Hence the value of this parameter should be small (e.g. less than 10).
optional int32 routing_cut_subset_size_for_tight_binary_relation_bound = 313 [default = 0];- Specified by:
getRoutingCutSubsetSizeForTightBinaryRelationBoundin interfaceSatParametersOrBuilder- Returns:
- The routingCutSubsetSizeForTightBinaryRelationBound.
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setRoutingCutSubsetSizeForTightBinaryRelationBound
Similar to above, but with a different algorithm producing better cuts, at the price of a higher O(2^n) complexity, where n is the subset size. Hence the value of this parameter should be small (e.g. less than 10).
optional int32 routing_cut_subset_size_for_tight_binary_relation_bound = 313 [default = 0];- Parameters:
value- The routingCutSubsetSizeForTightBinaryRelationBound to set.- Returns:
- This builder for chaining.
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clearRoutingCutSubsetSizeForTightBinaryRelationBound
Similar to above, but with a different algorithm producing better cuts, at the price of a higher O(2^n) complexity, where n is the subset size. Hence the value of this parameter should be small (e.g. less than 10).
optional int32 routing_cut_subset_size_for_tight_binary_relation_bound = 313 [default = 0];- Returns:
- This builder for chaining.
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hasRoutingCutSubsetSizeForExactBinaryRelationBound
public boolean hasRoutingCutSubsetSizeForExactBinaryRelationBound()Similar to above, but with an even stronger algorithm in O(n!). We try to be defensive and abort early or not run that often. Still the value of that parameter shouldn't really be much more than 10.
optional int32 routing_cut_subset_size_for_exact_binary_relation_bound = 316 [default = 8];- Specified by:
hasRoutingCutSubsetSizeForExactBinaryRelationBoundin interfaceSatParametersOrBuilder- Returns:
- Whether the routingCutSubsetSizeForExactBinaryRelationBound field is set.
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getRoutingCutSubsetSizeForExactBinaryRelationBound
public int getRoutingCutSubsetSizeForExactBinaryRelationBound()Similar to above, but with an even stronger algorithm in O(n!). We try to be defensive and abort early or not run that often. Still the value of that parameter shouldn't really be much more than 10.
optional int32 routing_cut_subset_size_for_exact_binary_relation_bound = 316 [default = 8];- Specified by:
getRoutingCutSubsetSizeForExactBinaryRelationBoundin interfaceSatParametersOrBuilder- Returns:
- The routingCutSubsetSizeForExactBinaryRelationBound.
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setRoutingCutSubsetSizeForExactBinaryRelationBound
Similar to above, but with an even stronger algorithm in O(n!). We try to be defensive and abort early or not run that often. Still the value of that parameter shouldn't really be much more than 10.
optional int32 routing_cut_subset_size_for_exact_binary_relation_bound = 316 [default = 8];- Parameters:
value- The routingCutSubsetSizeForExactBinaryRelationBound to set.- Returns:
- This builder for chaining.
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clearRoutingCutSubsetSizeForExactBinaryRelationBound
Similar to above, but with an even stronger algorithm in O(n!). We try to be defensive and abort early or not run that often. Still the value of that parameter shouldn't really be much more than 10.
optional int32 routing_cut_subset_size_for_exact_binary_relation_bound = 316 [default = 8];- Returns:
- This builder for chaining.
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hasRoutingCutSubsetSizeForShortestPathsBound
public boolean hasRoutingCutSubsetSizeForShortestPathsBound()Similar to routing_cut_subset_size_for_exact_binary_relation_bound but use a bound based on shortest path distances (which respect triangular inequality). This allows to derive bounds that are valid for any superset of a given subset. This is slow, so it shouldn't really be larger than 10.
optional int32 routing_cut_subset_size_for_shortest_paths_bound = 318 [default = 8];- Specified by:
hasRoutingCutSubsetSizeForShortestPathsBoundin interfaceSatParametersOrBuilder- Returns:
- Whether the routingCutSubsetSizeForShortestPathsBound field is set.
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getRoutingCutSubsetSizeForShortestPathsBound
public int getRoutingCutSubsetSizeForShortestPathsBound()Similar to routing_cut_subset_size_for_exact_binary_relation_bound but use a bound based on shortest path distances (which respect triangular inequality). This allows to derive bounds that are valid for any superset of a given subset. This is slow, so it shouldn't really be larger than 10.
optional int32 routing_cut_subset_size_for_shortest_paths_bound = 318 [default = 8];- Specified by:
getRoutingCutSubsetSizeForShortestPathsBoundin interfaceSatParametersOrBuilder- Returns:
- The routingCutSubsetSizeForShortestPathsBound.
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setRoutingCutSubsetSizeForShortestPathsBound
Similar to routing_cut_subset_size_for_exact_binary_relation_bound but use a bound based on shortest path distances (which respect triangular inequality). This allows to derive bounds that are valid for any superset of a given subset. This is slow, so it shouldn't really be larger than 10.
optional int32 routing_cut_subset_size_for_shortest_paths_bound = 318 [default = 8];- Parameters:
value- The routingCutSubsetSizeForShortestPathsBound to set.- Returns:
- This builder for chaining.
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clearRoutingCutSubsetSizeForShortestPathsBound
Similar to routing_cut_subset_size_for_exact_binary_relation_bound but use a bound based on shortest path distances (which respect triangular inequality). This allows to derive bounds that are valid for any superset of a given subset. This is slow, so it shouldn't really be larger than 10.
optional int32 routing_cut_subset_size_for_shortest_paths_bound = 318 [default = 8];- Returns:
- This builder for chaining.
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hasRoutingCutDpEffort
public boolean hasRoutingCutDpEffort()The amount of "effort" to spend in dynamic programming for computing routing cuts. This is in term of basic operations needed by the algorithm in the worst case, so a value like 1e8 should take less than a second to compute.
optional double routing_cut_dp_effort = 314 [default = 10000000];- Specified by:
hasRoutingCutDpEffortin interfaceSatParametersOrBuilder- Returns:
- Whether the routingCutDpEffort field is set.
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getRoutingCutDpEffort
public double getRoutingCutDpEffort()The amount of "effort" to spend in dynamic programming for computing routing cuts. This is in term of basic operations needed by the algorithm in the worst case, so a value like 1e8 should take less than a second to compute.
optional double routing_cut_dp_effort = 314 [default = 10000000];- Specified by:
getRoutingCutDpEffortin interfaceSatParametersOrBuilder- Returns:
- The routingCutDpEffort.
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setRoutingCutDpEffort
The amount of "effort" to spend in dynamic programming for computing routing cuts. This is in term of basic operations needed by the algorithm in the worst case, so a value like 1e8 should take less than a second to compute.
optional double routing_cut_dp_effort = 314 [default = 10000000];- Parameters:
value- The routingCutDpEffort to set.- Returns:
- This builder for chaining.
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clearRoutingCutDpEffort
The amount of "effort" to spend in dynamic programming for computing routing cuts. This is in term of basic operations needed by the algorithm in the worst case, so a value like 1e8 should take less than a second to compute.
optional double routing_cut_dp_effort = 314 [default = 10000000];- Returns:
- This builder for chaining.
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hasRoutingCutMaxInfeasiblePathLength
public boolean hasRoutingCutMaxInfeasiblePathLength()If the length of an infeasible path is less than this value, a cut will be added to exclude it.
optional int32 routing_cut_max_infeasible_path_length = 317 [default = 6];- Specified by:
hasRoutingCutMaxInfeasiblePathLengthin interfaceSatParametersOrBuilder- Returns:
- Whether the routingCutMaxInfeasiblePathLength field is set.
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getRoutingCutMaxInfeasiblePathLength
public int getRoutingCutMaxInfeasiblePathLength()If the length of an infeasible path is less than this value, a cut will be added to exclude it.
optional int32 routing_cut_max_infeasible_path_length = 317 [default = 6];- Specified by:
getRoutingCutMaxInfeasiblePathLengthin interfaceSatParametersOrBuilder- Returns:
- The routingCutMaxInfeasiblePathLength.
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setRoutingCutMaxInfeasiblePathLength
If the length of an infeasible path is less than this value, a cut will be added to exclude it.
optional int32 routing_cut_max_infeasible_path_length = 317 [default = 6];- Parameters:
value- The routingCutMaxInfeasiblePathLength to set.- Returns:
- This builder for chaining.
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clearRoutingCutMaxInfeasiblePathLength
If the length of an infeasible path is less than this value, a cut will be added to exclude it.
optional int32 routing_cut_max_infeasible_path_length = 317 [default = 6];- Returns:
- This builder for chaining.
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hasSearchBranching
public boolean hasSearchBranching()optional .operations_research.sat.SatParameters.SearchBranching search_branching = 82 [default = AUTOMATIC_SEARCH];- Specified by:
hasSearchBranchingin interfaceSatParametersOrBuilder- Returns:
- Whether the searchBranching field is set.
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getSearchBranching
optional .operations_research.sat.SatParameters.SearchBranching search_branching = 82 [default = AUTOMATIC_SEARCH];- Specified by:
getSearchBranchingin interfaceSatParametersOrBuilder- Returns:
- The searchBranching.
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setSearchBranching
optional .operations_research.sat.SatParameters.SearchBranching search_branching = 82 [default = AUTOMATIC_SEARCH];- Parameters:
value- The searchBranching to set.- Returns:
- This builder for chaining.
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clearSearchBranching
optional .operations_research.sat.SatParameters.SearchBranching search_branching = 82 [default = AUTOMATIC_SEARCH];- Returns:
- This builder for chaining.
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hasHintConflictLimit
public boolean hasHintConflictLimit()Conflict limit used in the phase that exploit the solution hint.
optional int32 hint_conflict_limit = 153 [default = 10];- Specified by:
hasHintConflictLimitin interfaceSatParametersOrBuilder- Returns:
- Whether the hintConflictLimit field is set.
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getHintConflictLimit
public int getHintConflictLimit()Conflict limit used in the phase that exploit the solution hint.
optional int32 hint_conflict_limit = 153 [default = 10];- Specified by:
getHintConflictLimitin interfaceSatParametersOrBuilder- Returns:
- The hintConflictLimit.
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setHintConflictLimit
Conflict limit used in the phase that exploit the solution hint.
optional int32 hint_conflict_limit = 153 [default = 10];- Parameters:
value- The hintConflictLimit to set.- Returns:
- This builder for chaining.
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clearHintConflictLimit
Conflict limit used in the phase that exploit the solution hint.
optional int32 hint_conflict_limit = 153 [default = 10];- Returns:
- This builder for chaining.
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hasRepairHint
public boolean hasRepairHint()If true, the solver tries to repair the solution given in the hint. This search terminates after the 'hint_conflict_limit' is reached and the solver switches to regular search. If false, then we do a FIXED_SEARCH using the hint until the hint_conflict_limit is reached.
optional bool repair_hint = 167 [default = false];- Specified by:
hasRepairHintin interfaceSatParametersOrBuilder- Returns:
- Whether the repairHint field is set.
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getRepairHint
public boolean getRepairHint()If true, the solver tries to repair the solution given in the hint. This search terminates after the 'hint_conflict_limit' is reached and the solver switches to regular search. If false, then we do a FIXED_SEARCH using the hint until the hint_conflict_limit is reached.
optional bool repair_hint = 167 [default = false];- Specified by:
getRepairHintin interfaceSatParametersOrBuilder- Returns:
- The repairHint.
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setRepairHint
If true, the solver tries to repair the solution given in the hint. This search terminates after the 'hint_conflict_limit' is reached and the solver switches to regular search. If false, then we do a FIXED_SEARCH using the hint until the hint_conflict_limit is reached.
optional bool repair_hint = 167 [default = false];- Parameters:
value- The repairHint to set.- Returns:
- This builder for chaining.
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clearRepairHint
If true, the solver tries to repair the solution given in the hint. This search terminates after the 'hint_conflict_limit' is reached and the solver switches to regular search. If false, then we do a FIXED_SEARCH using the hint until the hint_conflict_limit is reached.
optional bool repair_hint = 167 [default = false];- Returns:
- This builder for chaining.
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hasFixVariablesToTheirHintedValue
public boolean hasFixVariablesToTheirHintedValue()If true, variables appearing in the solution hints will be fixed to their hinted value.
optional bool fix_variables_to_their_hinted_value = 192 [default = false];- Specified by:
hasFixVariablesToTheirHintedValuein interfaceSatParametersOrBuilder- Returns:
- Whether the fixVariablesToTheirHintedValue field is set.
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getFixVariablesToTheirHintedValue
public boolean getFixVariablesToTheirHintedValue()If true, variables appearing in the solution hints will be fixed to their hinted value.
optional bool fix_variables_to_their_hinted_value = 192 [default = false];- Specified by:
getFixVariablesToTheirHintedValuein interfaceSatParametersOrBuilder- Returns:
- The fixVariablesToTheirHintedValue.
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setFixVariablesToTheirHintedValue
If true, variables appearing in the solution hints will be fixed to their hinted value.
optional bool fix_variables_to_their_hinted_value = 192 [default = false];- Parameters:
value- The fixVariablesToTheirHintedValue to set.- Returns:
- This builder for chaining.
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clearFixVariablesToTheirHintedValue
If true, variables appearing in the solution hints will be fixed to their hinted value.
optional bool fix_variables_to_their_hinted_value = 192 [default = false];- Returns:
- This builder for chaining.
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hasUseProbingSearch
public boolean hasUseProbingSearch()If true, search will continuously probe Boolean variables, and integer variable bounds. This parameter is set to true in parallel on the probing worker.
optional bool use_probing_search = 176 [default = false];- Specified by:
hasUseProbingSearchin interfaceSatParametersOrBuilder- Returns:
- Whether the useProbingSearch field is set.
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getUseProbingSearch
public boolean getUseProbingSearch()If true, search will continuously probe Boolean variables, and integer variable bounds. This parameter is set to true in parallel on the probing worker.
optional bool use_probing_search = 176 [default = false];- Specified by:
getUseProbingSearchin interfaceSatParametersOrBuilder- Returns:
- The useProbingSearch.
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setUseProbingSearch
If true, search will continuously probe Boolean variables, and integer variable bounds. This parameter is set to true in parallel on the probing worker.
optional bool use_probing_search = 176 [default = false];- Parameters:
value- The useProbingSearch to set.- Returns:
- This builder for chaining.
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clearUseProbingSearch
If true, search will continuously probe Boolean variables, and integer variable bounds. This parameter is set to true in parallel on the probing worker.
optional bool use_probing_search = 176 [default = false];- Returns:
- This builder for chaining.
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hasUseExtendedProbing
public boolean hasUseExtendedProbing()Use extended probing (probe bool_or, at_most_one, exactly_one).
optional bool use_extended_probing = 269 [default = true];- Specified by:
hasUseExtendedProbingin interfaceSatParametersOrBuilder- Returns:
- Whether the useExtendedProbing field is set.
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getUseExtendedProbing
public boolean getUseExtendedProbing()Use extended probing (probe bool_or, at_most_one, exactly_one).
optional bool use_extended_probing = 269 [default = true];- Specified by:
getUseExtendedProbingin interfaceSatParametersOrBuilder- Returns:
- The useExtendedProbing.
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setUseExtendedProbing
Use extended probing (probe bool_or, at_most_one, exactly_one).
optional bool use_extended_probing = 269 [default = true];- Parameters:
value- The useExtendedProbing to set.- Returns:
- This builder for chaining.
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clearUseExtendedProbing
Use extended probing (probe bool_or, at_most_one, exactly_one).
optional bool use_extended_probing = 269 [default = true];- Returns:
- This builder for chaining.
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hasProbingNumCombinationsLimit
public boolean hasProbingNumCombinationsLimit()How many combinations of pairs or triplets of variables we want to scan.
optional int32 probing_num_combinations_limit = 272 [default = 20000];- Specified by:
hasProbingNumCombinationsLimitin interfaceSatParametersOrBuilder- Returns:
- Whether the probingNumCombinationsLimit field is set.
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getProbingNumCombinationsLimit
public int getProbingNumCombinationsLimit()How many combinations of pairs or triplets of variables we want to scan.
optional int32 probing_num_combinations_limit = 272 [default = 20000];- Specified by:
getProbingNumCombinationsLimitin interfaceSatParametersOrBuilder- Returns:
- The probingNumCombinationsLimit.
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setProbingNumCombinationsLimit
How many combinations of pairs or triplets of variables we want to scan.
optional int32 probing_num_combinations_limit = 272 [default = 20000];- Parameters:
value- The probingNumCombinationsLimit to set.- Returns:
- This builder for chaining.
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clearProbingNumCombinationsLimit
How many combinations of pairs or triplets of variables we want to scan.
optional int32 probing_num_combinations_limit = 272 [default = 20000];- Returns:
- This builder for chaining.
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hasShavingDeterministicTimeInProbingSearch
public boolean hasShavingDeterministicTimeInProbingSearch()Add a shaving phase (where the solver tries to prove that the lower or upper bound of a variable are infeasible) to the probing search. (<= 0 disables it).
optional double shaving_deterministic_time_in_probing_search = 204 [default = 0.001];- Specified by:
hasShavingDeterministicTimeInProbingSearchin interfaceSatParametersOrBuilder- Returns:
- Whether the shavingDeterministicTimeInProbingSearch field is set.
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getShavingDeterministicTimeInProbingSearch
public double getShavingDeterministicTimeInProbingSearch()Add a shaving phase (where the solver tries to prove that the lower or upper bound of a variable are infeasible) to the probing search. (<= 0 disables it).
optional double shaving_deterministic_time_in_probing_search = 204 [default = 0.001];- Specified by:
getShavingDeterministicTimeInProbingSearchin interfaceSatParametersOrBuilder- Returns:
- The shavingDeterministicTimeInProbingSearch.
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setShavingDeterministicTimeInProbingSearch
Add a shaving phase (where the solver tries to prove that the lower or upper bound of a variable are infeasible) to the probing search. (<= 0 disables it).
optional double shaving_deterministic_time_in_probing_search = 204 [default = 0.001];- Parameters:
value- The shavingDeterministicTimeInProbingSearch to set.- Returns:
- This builder for chaining.
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clearShavingDeterministicTimeInProbingSearch
Add a shaving phase (where the solver tries to prove that the lower or upper bound of a variable are infeasible) to the probing search. (<= 0 disables it).
optional double shaving_deterministic_time_in_probing_search = 204 [default = 0.001];- Returns:
- This builder for chaining.
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hasShavingSearchDeterministicTime
public boolean hasShavingSearchDeterministicTime()Specifies the amount of deterministic time spent of each try at shaving a bound in the shaving search.
optional double shaving_search_deterministic_time = 205 [default = 0.1];- Specified by:
hasShavingSearchDeterministicTimein interfaceSatParametersOrBuilder- Returns:
- Whether the shavingSearchDeterministicTime field is set.
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getShavingSearchDeterministicTime
public double getShavingSearchDeterministicTime()Specifies the amount of deterministic time spent of each try at shaving a bound in the shaving search.
optional double shaving_search_deterministic_time = 205 [default = 0.1];- Specified by:
getShavingSearchDeterministicTimein interfaceSatParametersOrBuilder- Returns:
- The shavingSearchDeterministicTime.
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setShavingSearchDeterministicTime
Specifies the amount of deterministic time spent of each try at shaving a bound in the shaving search.
optional double shaving_search_deterministic_time = 205 [default = 0.1];- Parameters:
value- The shavingSearchDeterministicTime to set.- Returns:
- This builder for chaining.
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clearShavingSearchDeterministicTime
Specifies the amount of deterministic time spent of each try at shaving a bound in the shaving search.
optional double shaving_search_deterministic_time = 205 [default = 0.1];- Returns:
- This builder for chaining.
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hasShavingSearchThreshold
public boolean hasShavingSearchThreshold()Specifies the threshold between two modes in the shaving procedure. If the range of the variable/objective is less than this threshold, then the shaving procedure will try to remove values one by one. Otherwise, it will try to remove one range at a time.
optional int64 shaving_search_threshold = 290 [default = 64];- Specified by:
hasShavingSearchThresholdin interfaceSatParametersOrBuilder- Returns:
- Whether the shavingSearchThreshold field is set.
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getShavingSearchThreshold
public long getShavingSearchThreshold()Specifies the threshold between two modes in the shaving procedure. If the range of the variable/objective is less than this threshold, then the shaving procedure will try to remove values one by one. Otherwise, it will try to remove one range at a time.
optional int64 shaving_search_threshold = 290 [default = 64];- Specified by:
getShavingSearchThresholdin interfaceSatParametersOrBuilder- Returns:
- The shavingSearchThreshold.
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setShavingSearchThreshold
Specifies the threshold between two modes in the shaving procedure. If the range of the variable/objective is less than this threshold, then the shaving procedure will try to remove values one by one. Otherwise, it will try to remove one range at a time.
optional int64 shaving_search_threshold = 290 [default = 64];- Parameters:
value- The shavingSearchThreshold to set.- Returns:
- This builder for chaining.
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clearShavingSearchThreshold
Specifies the threshold between two modes in the shaving procedure. If the range of the variable/objective is less than this threshold, then the shaving procedure will try to remove values one by one. Otherwise, it will try to remove one range at a time.
optional int64 shaving_search_threshold = 290 [default = 64];- Returns:
- This builder for chaining.
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hasUseObjectiveLbSearch
public boolean hasUseObjectiveLbSearch()If true, search will search in ascending max objective value (when minimizing) starting from the lower bound of the objective.
optional bool use_objective_lb_search = 228 [default = false];- Specified by:
hasUseObjectiveLbSearchin interfaceSatParametersOrBuilder- Returns:
- Whether the useObjectiveLbSearch field is set.
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getUseObjectiveLbSearch
public boolean getUseObjectiveLbSearch()If true, search will search in ascending max objective value (when minimizing) starting from the lower bound of the objective.
optional bool use_objective_lb_search = 228 [default = false];- Specified by:
getUseObjectiveLbSearchin interfaceSatParametersOrBuilder- Returns:
- The useObjectiveLbSearch.
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setUseObjectiveLbSearch
If true, search will search in ascending max objective value (when minimizing) starting from the lower bound of the objective.
optional bool use_objective_lb_search = 228 [default = false];- Parameters:
value- The useObjectiveLbSearch to set.- Returns:
- This builder for chaining.
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clearUseObjectiveLbSearch
If true, search will search in ascending max objective value (when minimizing) starting from the lower bound of the objective.
optional bool use_objective_lb_search = 228 [default = false];- Returns:
- This builder for chaining.
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hasUseObjectiveShavingSearch
public boolean hasUseObjectiveShavingSearch()This search differs from the previous search as it will not use assumptions to bound the objective, and it will recreate a full model with the hardcoded objective value.
optional bool use_objective_shaving_search = 253 [default = false];- Specified by:
hasUseObjectiveShavingSearchin interfaceSatParametersOrBuilder- Returns:
- Whether the useObjectiveShavingSearch field is set.
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getUseObjectiveShavingSearch
public boolean getUseObjectiveShavingSearch()This search differs from the previous search as it will not use assumptions to bound the objective, and it will recreate a full model with the hardcoded objective value.
optional bool use_objective_shaving_search = 253 [default = false];- Specified by:
getUseObjectiveShavingSearchin interfaceSatParametersOrBuilder- Returns:
- The useObjectiveShavingSearch.
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setUseObjectiveShavingSearch
This search differs from the previous search as it will not use assumptions to bound the objective, and it will recreate a full model with the hardcoded objective value.
optional bool use_objective_shaving_search = 253 [default = false];- Parameters:
value- The useObjectiveShavingSearch to set.- Returns:
- This builder for chaining.
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clearUseObjectiveShavingSearch
This search differs from the previous search as it will not use assumptions to bound the objective, and it will recreate a full model with the hardcoded objective value.
optional bool use_objective_shaving_search = 253 [default = false];- Returns:
- This builder for chaining.
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hasVariablesShavingLevel
public boolean hasVariablesShavingLevel()This search takes all Boolean or integer variables, and maximize or minimize them in order to reduce their domain. -1 is automatic, otherwise value 0 disables it, and 1, 2, or 3 changes something.
optional int32 variables_shaving_level = 289 [default = -1];- Specified by:
hasVariablesShavingLevelin interfaceSatParametersOrBuilder- Returns:
- Whether the variablesShavingLevel field is set.
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getVariablesShavingLevel
public int getVariablesShavingLevel()This search takes all Boolean or integer variables, and maximize or minimize them in order to reduce their domain. -1 is automatic, otherwise value 0 disables it, and 1, 2, or 3 changes something.
optional int32 variables_shaving_level = 289 [default = -1];- Specified by:
getVariablesShavingLevelin interfaceSatParametersOrBuilder- Returns:
- The variablesShavingLevel.
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setVariablesShavingLevel
This search takes all Boolean or integer variables, and maximize or minimize them in order to reduce their domain. -1 is automatic, otherwise value 0 disables it, and 1, 2, or 3 changes something.
optional int32 variables_shaving_level = 289 [default = -1];- Parameters:
value- The variablesShavingLevel to set.- Returns:
- This builder for chaining.
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clearVariablesShavingLevel
This search takes all Boolean or integer variables, and maximize or minimize them in order to reduce their domain. -1 is automatic, otherwise value 0 disables it, and 1, 2, or 3 changes something.
optional int32 variables_shaving_level = 289 [default = -1];- Returns:
- This builder for chaining.
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hasPseudoCostReliabilityThreshold
public boolean hasPseudoCostReliabilityThreshold()The solver ignores the pseudo costs of variables with number of recordings less than this threshold.
optional int64 pseudo_cost_reliability_threshold = 123 [default = 100];- Specified by:
hasPseudoCostReliabilityThresholdin interfaceSatParametersOrBuilder- Returns:
- Whether the pseudoCostReliabilityThreshold field is set.
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getPseudoCostReliabilityThreshold
public long getPseudoCostReliabilityThreshold()The solver ignores the pseudo costs of variables with number of recordings less than this threshold.
optional int64 pseudo_cost_reliability_threshold = 123 [default = 100];- Specified by:
getPseudoCostReliabilityThresholdin interfaceSatParametersOrBuilder- Returns:
- The pseudoCostReliabilityThreshold.
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setPseudoCostReliabilityThreshold
The solver ignores the pseudo costs of variables with number of recordings less than this threshold.
optional int64 pseudo_cost_reliability_threshold = 123 [default = 100];- Parameters:
value- The pseudoCostReliabilityThreshold to set.- Returns:
- This builder for chaining.
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clearPseudoCostReliabilityThreshold
The solver ignores the pseudo costs of variables with number of recordings less than this threshold.
optional int64 pseudo_cost_reliability_threshold = 123 [default = 100];- Returns:
- This builder for chaining.
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hasOptimizeWithCore
public boolean hasOptimizeWithCore()The default optimization method is a simple "linear scan", each time trying to find a better solution than the previous one. If this is true, then we use a core-based approach (like in max-SAT) when we try to increase the lower bound instead.
optional bool optimize_with_core = 83 [default = false];- Specified by:
hasOptimizeWithCorein interfaceSatParametersOrBuilder- Returns:
- Whether the optimizeWithCore field is set.
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getOptimizeWithCore
public boolean getOptimizeWithCore()The default optimization method is a simple "linear scan", each time trying to find a better solution than the previous one. If this is true, then we use a core-based approach (like in max-SAT) when we try to increase the lower bound instead.
optional bool optimize_with_core = 83 [default = false];- Specified by:
getOptimizeWithCorein interfaceSatParametersOrBuilder- Returns:
- The optimizeWithCore.
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setOptimizeWithCore
The default optimization method is a simple "linear scan", each time trying to find a better solution than the previous one. If this is true, then we use a core-based approach (like in max-SAT) when we try to increase the lower bound instead.
optional bool optimize_with_core = 83 [default = false];- Parameters:
value- The optimizeWithCore to set.- Returns:
- This builder for chaining.
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clearOptimizeWithCore
The default optimization method is a simple "linear scan", each time trying to find a better solution than the previous one. If this is true, then we use a core-based approach (like in max-SAT) when we try to increase the lower bound instead.
optional bool optimize_with_core = 83 [default = false];- Returns:
- This builder for chaining.
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hasOptimizeWithLbTreeSearch
public boolean hasOptimizeWithLbTreeSearch()Do a more conventional tree search (by opposition to SAT based one) where we keep all the explored node in a tree. This is meant to be used in a portfolio and focus on improving the objective lower bound. Keeping the whole tree allow us to report a better objective lower bound coming from the worst open node in the tree.
optional bool optimize_with_lb_tree_search = 188 [default = false];- Specified by:
hasOptimizeWithLbTreeSearchin interfaceSatParametersOrBuilder- Returns:
- Whether the optimizeWithLbTreeSearch field is set.
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getOptimizeWithLbTreeSearch
public boolean getOptimizeWithLbTreeSearch()Do a more conventional tree search (by opposition to SAT based one) where we keep all the explored node in a tree. This is meant to be used in a portfolio and focus on improving the objective lower bound. Keeping the whole tree allow us to report a better objective lower bound coming from the worst open node in the tree.
optional bool optimize_with_lb_tree_search = 188 [default = false];- Specified by:
getOptimizeWithLbTreeSearchin interfaceSatParametersOrBuilder- Returns:
- The optimizeWithLbTreeSearch.
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setOptimizeWithLbTreeSearch
Do a more conventional tree search (by opposition to SAT based one) where we keep all the explored node in a tree. This is meant to be used in a portfolio and focus on improving the objective lower bound. Keeping the whole tree allow us to report a better objective lower bound coming from the worst open node in the tree.
optional bool optimize_with_lb_tree_search = 188 [default = false];- Parameters:
value- The optimizeWithLbTreeSearch to set.- Returns:
- This builder for chaining.
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clearOptimizeWithLbTreeSearch
Do a more conventional tree search (by opposition to SAT based one) where we keep all the explored node in a tree. This is meant to be used in a portfolio and focus on improving the objective lower bound. Keeping the whole tree allow us to report a better objective lower bound coming from the worst open node in the tree.
optional bool optimize_with_lb_tree_search = 188 [default = false];- Returns:
- This builder for chaining.
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hasSaveLpBasisInLbTreeSearch
public boolean hasSaveLpBasisInLbTreeSearch()Experimental. Save the current LP basis at each node of the search tree so that when we jump around, we can load it and reduce the number of LP iterations needed. It currently works okay if we do not change the lp with cuts or simplification... More work is needed to make it robust in all cases.
optional bool save_lp_basis_in_lb_tree_search = 284 [default = false];- Specified by:
hasSaveLpBasisInLbTreeSearchin interfaceSatParametersOrBuilder- Returns:
- Whether the saveLpBasisInLbTreeSearch field is set.
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getSaveLpBasisInLbTreeSearch
public boolean getSaveLpBasisInLbTreeSearch()Experimental. Save the current LP basis at each node of the search tree so that when we jump around, we can load it and reduce the number of LP iterations needed. It currently works okay if we do not change the lp with cuts or simplification... More work is needed to make it robust in all cases.
optional bool save_lp_basis_in_lb_tree_search = 284 [default = false];- Specified by:
getSaveLpBasisInLbTreeSearchin interfaceSatParametersOrBuilder- Returns:
- The saveLpBasisInLbTreeSearch.
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setSaveLpBasisInLbTreeSearch
Experimental. Save the current LP basis at each node of the search tree so that when we jump around, we can load it and reduce the number of LP iterations needed. It currently works okay if we do not change the lp with cuts or simplification... More work is needed to make it robust in all cases.
optional bool save_lp_basis_in_lb_tree_search = 284 [default = false];- Parameters:
value- The saveLpBasisInLbTreeSearch to set.- Returns:
- This builder for chaining.
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clearSaveLpBasisInLbTreeSearch
Experimental. Save the current LP basis at each node of the search tree so that when we jump around, we can load it and reduce the number of LP iterations needed. It currently works okay if we do not change the lp with cuts or simplification... More work is needed to make it robust in all cases.
optional bool save_lp_basis_in_lb_tree_search = 284 [default = false];- Returns:
- This builder for chaining.
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hasBinarySearchNumConflicts
public boolean hasBinarySearchNumConflicts()If non-negative, perform a binary search on the objective variable in order to find an [min, max] interval outside of which the solver proved unsat/sat under this amount of conflict. This can quickly reduce the objective domain on some problems.
optional int32 binary_search_num_conflicts = 99 [default = -1];- Specified by:
hasBinarySearchNumConflictsin interfaceSatParametersOrBuilder- Returns:
- Whether the binarySearchNumConflicts field is set.
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getBinarySearchNumConflicts
public int getBinarySearchNumConflicts()If non-negative, perform a binary search on the objective variable in order to find an [min, max] interval outside of which the solver proved unsat/sat under this amount of conflict. This can quickly reduce the objective domain on some problems.
optional int32 binary_search_num_conflicts = 99 [default = -1];- Specified by:
getBinarySearchNumConflictsin interfaceSatParametersOrBuilder- Returns:
- The binarySearchNumConflicts.
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setBinarySearchNumConflicts
If non-negative, perform a binary search on the objective variable in order to find an [min, max] interval outside of which the solver proved unsat/sat under this amount of conflict. This can quickly reduce the objective domain on some problems.
optional int32 binary_search_num_conflicts = 99 [default = -1];- Parameters:
value- The binarySearchNumConflicts to set.- Returns:
- This builder for chaining.
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clearBinarySearchNumConflicts
If non-negative, perform a binary search on the objective variable in order to find an [min, max] interval outside of which the solver proved unsat/sat under this amount of conflict. This can quickly reduce the objective domain on some problems.
optional int32 binary_search_num_conflicts = 99 [default = -1];- Returns:
- This builder for chaining.
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hasOptimizeWithMaxHs
public boolean hasOptimizeWithMaxHs()This has no effect if optimize_with_core is false. If true, use a different core-based algorithm similar to the max-HS algo for max-SAT. This is a hybrid MIP/CP approach and it uses a MIP solver in addition to the CP/SAT one. This is also related to the PhD work of tobyodavies@ "Automatic Logic-Based Benders Decomposition with MiniZinc" http://aaai.org/ocs/index.php/AAAI/AAAI17/paper/view/14489
optional bool optimize_with_max_hs = 85 [default = false];- Specified by:
hasOptimizeWithMaxHsin interfaceSatParametersOrBuilder- Returns:
- Whether the optimizeWithMaxHs field is set.
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getOptimizeWithMaxHs
public boolean getOptimizeWithMaxHs()This has no effect if optimize_with_core is false. If true, use a different core-based algorithm similar to the max-HS algo for max-SAT. This is a hybrid MIP/CP approach and it uses a MIP solver in addition to the CP/SAT one. This is also related to the PhD work of tobyodavies@ "Automatic Logic-Based Benders Decomposition with MiniZinc" http://aaai.org/ocs/index.php/AAAI/AAAI17/paper/view/14489
optional bool optimize_with_max_hs = 85 [default = false];- Specified by:
getOptimizeWithMaxHsin interfaceSatParametersOrBuilder- Returns:
- The optimizeWithMaxHs.
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setOptimizeWithMaxHs
This has no effect if optimize_with_core is false. If true, use a different core-based algorithm similar to the max-HS algo for max-SAT. This is a hybrid MIP/CP approach and it uses a MIP solver in addition to the CP/SAT one. This is also related to the PhD work of tobyodavies@ "Automatic Logic-Based Benders Decomposition with MiniZinc" http://aaai.org/ocs/index.php/AAAI/AAAI17/paper/view/14489
optional bool optimize_with_max_hs = 85 [default = false];- Parameters:
value- The optimizeWithMaxHs to set.- Returns:
- This builder for chaining.
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clearOptimizeWithMaxHs
This has no effect if optimize_with_core is false. If true, use a different core-based algorithm similar to the max-HS algo for max-SAT. This is a hybrid MIP/CP approach and it uses a MIP solver in addition to the CP/SAT one. This is also related to the PhD work of tobyodavies@ "Automatic Logic-Based Benders Decomposition with MiniZinc" http://aaai.org/ocs/index.php/AAAI/AAAI17/paper/view/14489
optional bool optimize_with_max_hs = 85 [default = false];- Returns:
- This builder for chaining.
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hasUseFeasibilityJump
public boolean hasUseFeasibilityJump()Parameters for an heuristic similar to the one described in the paper: "Feasibility Jump: an LP-free Lagrangian MIP heuristic", Bjørnar Luteberget, Giorgio Sartor, 2023, Mathematical Programming Computation.
optional bool use_feasibility_jump = 265 [default = true];- Specified by:
hasUseFeasibilityJumpin interfaceSatParametersOrBuilder- Returns:
- Whether the useFeasibilityJump field is set.
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getUseFeasibilityJump
public boolean getUseFeasibilityJump()Parameters for an heuristic similar to the one described in the paper: "Feasibility Jump: an LP-free Lagrangian MIP heuristic", Bjørnar Luteberget, Giorgio Sartor, 2023, Mathematical Programming Computation.
optional bool use_feasibility_jump = 265 [default = true];- Specified by:
getUseFeasibilityJumpin interfaceSatParametersOrBuilder- Returns:
- The useFeasibilityJump.
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setUseFeasibilityJump
Parameters for an heuristic similar to the one described in the paper: "Feasibility Jump: an LP-free Lagrangian MIP heuristic", Bjørnar Luteberget, Giorgio Sartor, 2023, Mathematical Programming Computation.
optional bool use_feasibility_jump = 265 [default = true];- Parameters:
value- The useFeasibilityJump to set.- Returns:
- This builder for chaining.
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clearUseFeasibilityJump
Parameters for an heuristic similar to the one described in the paper: "Feasibility Jump: an LP-free Lagrangian MIP heuristic", Bjørnar Luteberget, Giorgio Sartor, 2023, Mathematical Programming Computation.
optional bool use_feasibility_jump = 265 [default = true];- Returns:
- This builder for chaining.
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hasUseLsOnly
public boolean hasUseLsOnly()Disable every other type of subsolver, setting this turns CP-SAT into a pure local-search solver.
optional bool use_ls_only = 240 [default = false];- Specified by:
hasUseLsOnlyin interfaceSatParametersOrBuilder- Returns:
- Whether the useLsOnly field is set.
-
getUseLsOnly
public boolean getUseLsOnly()Disable every other type of subsolver, setting this turns CP-SAT into a pure local-search solver.
optional bool use_ls_only = 240 [default = false];- Specified by:
getUseLsOnlyin interfaceSatParametersOrBuilder- Returns:
- The useLsOnly.
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setUseLsOnly
Disable every other type of subsolver, setting this turns CP-SAT into a pure local-search solver.
optional bool use_ls_only = 240 [default = false];- Parameters:
value- The useLsOnly to set.- Returns:
- This builder for chaining.
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clearUseLsOnly
Disable every other type of subsolver, setting this turns CP-SAT into a pure local-search solver.
optional bool use_ls_only = 240 [default = false];- Returns:
- This builder for chaining.
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hasFeasibilityJumpDecay
public boolean hasFeasibilityJumpDecay()On each restart, we randomly choose if we use decay (with this parameter) or no decay.
optional double feasibility_jump_decay = 242 [default = 0.95];- Specified by:
hasFeasibilityJumpDecayin interfaceSatParametersOrBuilder- Returns:
- Whether the feasibilityJumpDecay field is set.
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getFeasibilityJumpDecay
public double getFeasibilityJumpDecay()On each restart, we randomly choose if we use decay (with this parameter) or no decay.
optional double feasibility_jump_decay = 242 [default = 0.95];- Specified by:
getFeasibilityJumpDecayin interfaceSatParametersOrBuilder- Returns:
- The feasibilityJumpDecay.
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setFeasibilityJumpDecay
On each restart, we randomly choose if we use decay (with this parameter) or no decay.
optional double feasibility_jump_decay = 242 [default = 0.95];- Parameters:
value- The feasibilityJumpDecay to set.- Returns:
- This builder for chaining.
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clearFeasibilityJumpDecay
On each restart, we randomly choose if we use decay (with this parameter) or no decay.
optional double feasibility_jump_decay = 242 [default = 0.95];- Returns:
- This builder for chaining.
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hasFeasibilityJumpLinearizationLevel
public boolean hasFeasibilityJumpLinearizationLevel()How much do we linearize the problem in the local search code.
optional int32 feasibility_jump_linearization_level = 257 [default = 2];- Specified by:
hasFeasibilityJumpLinearizationLevelin interfaceSatParametersOrBuilder- Returns:
- Whether the feasibilityJumpLinearizationLevel field is set.
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getFeasibilityJumpLinearizationLevel
public int getFeasibilityJumpLinearizationLevel()How much do we linearize the problem in the local search code.
optional int32 feasibility_jump_linearization_level = 257 [default = 2];- Specified by:
getFeasibilityJumpLinearizationLevelin interfaceSatParametersOrBuilder- Returns:
- The feasibilityJumpLinearizationLevel.
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setFeasibilityJumpLinearizationLevel
How much do we linearize the problem in the local search code.
optional int32 feasibility_jump_linearization_level = 257 [default = 2];- Parameters:
value- The feasibilityJumpLinearizationLevel to set.- Returns:
- This builder for chaining.
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clearFeasibilityJumpLinearizationLevel
How much do we linearize the problem in the local search code.
optional int32 feasibility_jump_linearization_level = 257 [default = 2];- Returns:
- This builder for chaining.
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hasFeasibilityJumpRestartFactor
public boolean hasFeasibilityJumpRestartFactor()This is a factor that directly influence the work before each restart. Increasing it leads to longer restart.
optional int32 feasibility_jump_restart_factor = 258 [default = 1];- Specified by:
hasFeasibilityJumpRestartFactorin interfaceSatParametersOrBuilder- Returns:
- Whether the feasibilityJumpRestartFactor field is set.
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getFeasibilityJumpRestartFactor
public int getFeasibilityJumpRestartFactor()This is a factor that directly influence the work before each restart. Increasing it leads to longer restart.
optional int32 feasibility_jump_restart_factor = 258 [default = 1];- Specified by:
getFeasibilityJumpRestartFactorin interfaceSatParametersOrBuilder- Returns:
- The feasibilityJumpRestartFactor.
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setFeasibilityJumpRestartFactor
This is a factor that directly influence the work before each restart. Increasing it leads to longer restart.
optional int32 feasibility_jump_restart_factor = 258 [default = 1];- Parameters:
value- The feasibilityJumpRestartFactor to set.- Returns:
- This builder for chaining.
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clearFeasibilityJumpRestartFactor
This is a factor that directly influence the work before each restart. Increasing it leads to longer restart.
optional int32 feasibility_jump_restart_factor = 258 [default = 1];- Returns:
- This builder for chaining.
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hasFeasibilityJumpBatchDtime
public boolean hasFeasibilityJumpBatchDtime()How much dtime for each LS batch.
optional double feasibility_jump_batch_dtime = 292 [default = 0.1];- Specified by:
hasFeasibilityJumpBatchDtimein interfaceSatParametersOrBuilder- Returns:
- Whether the feasibilityJumpBatchDtime field is set.
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getFeasibilityJumpBatchDtime
public double getFeasibilityJumpBatchDtime()How much dtime for each LS batch.
optional double feasibility_jump_batch_dtime = 292 [default = 0.1];- Specified by:
getFeasibilityJumpBatchDtimein interfaceSatParametersOrBuilder- Returns:
- The feasibilityJumpBatchDtime.
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setFeasibilityJumpBatchDtime
How much dtime for each LS batch.
optional double feasibility_jump_batch_dtime = 292 [default = 0.1];- Parameters:
value- The feasibilityJumpBatchDtime to set.- Returns:
- This builder for chaining.
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clearFeasibilityJumpBatchDtime
How much dtime for each LS batch.
optional double feasibility_jump_batch_dtime = 292 [default = 0.1];- Returns:
- This builder for chaining.
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hasFeasibilityJumpVarRandomizationProbability
public boolean hasFeasibilityJumpVarRandomizationProbability()Probability for a variable to have a non default value upon restarts or perturbations.
optional double feasibility_jump_var_randomization_probability = 247 [default = 0.05];- Specified by:
hasFeasibilityJumpVarRandomizationProbabilityin interfaceSatParametersOrBuilder- Returns:
- Whether the feasibilityJumpVarRandomizationProbability field is set.
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getFeasibilityJumpVarRandomizationProbability
public double getFeasibilityJumpVarRandomizationProbability()Probability for a variable to have a non default value upon restarts or perturbations.
optional double feasibility_jump_var_randomization_probability = 247 [default = 0.05];- Specified by:
getFeasibilityJumpVarRandomizationProbabilityin interfaceSatParametersOrBuilder- Returns:
- The feasibilityJumpVarRandomizationProbability.
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setFeasibilityJumpVarRandomizationProbability
Probability for a variable to have a non default value upon restarts or perturbations.
optional double feasibility_jump_var_randomization_probability = 247 [default = 0.05];- Parameters:
value- The feasibilityJumpVarRandomizationProbability to set.- Returns:
- This builder for chaining.
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clearFeasibilityJumpVarRandomizationProbability
Probability for a variable to have a non default value upon restarts or perturbations.
optional double feasibility_jump_var_randomization_probability = 247 [default = 0.05];- Returns:
- This builder for chaining.
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hasFeasibilityJumpVarPerburbationRangeRatio
public boolean hasFeasibilityJumpVarPerburbationRangeRatio()Max distance between the default value and the pertubated value relative to the range of the domain of the variable.
optional double feasibility_jump_var_perburbation_range_ratio = 248 [default = 0.2];- Specified by:
hasFeasibilityJumpVarPerburbationRangeRatioin interfaceSatParametersOrBuilder- Returns:
- Whether the feasibilityJumpVarPerburbationRangeRatio field is set.
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getFeasibilityJumpVarPerburbationRangeRatio
public double getFeasibilityJumpVarPerburbationRangeRatio()Max distance between the default value and the pertubated value relative to the range of the domain of the variable.
optional double feasibility_jump_var_perburbation_range_ratio = 248 [default = 0.2];- Specified by:
getFeasibilityJumpVarPerburbationRangeRatioin interfaceSatParametersOrBuilder- Returns:
- The feasibilityJumpVarPerburbationRangeRatio.
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setFeasibilityJumpVarPerburbationRangeRatio
Max distance between the default value and the pertubated value relative to the range of the domain of the variable.
optional double feasibility_jump_var_perburbation_range_ratio = 248 [default = 0.2];- Parameters:
value- The feasibilityJumpVarPerburbationRangeRatio to set.- Returns:
- This builder for chaining.
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clearFeasibilityJumpVarPerburbationRangeRatio
Max distance between the default value and the pertubated value relative to the range of the domain of the variable.
optional double feasibility_jump_var_perburbation_range_ratio = 248 [default = 0.2];- Returns:
- This builder for chaining.
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hasFeasibilityJumpEnableRestarts
public boolean hasFeasibilityJumpEnableRestarts()When stagnating, feasibility jump will either restart from a default solution (with some possible randomization), or randomly pertubate the current solution. This parameter selects the first option.
optional bool feasibility_jump_enable_restarts = 250 [default = true];- Specified by:
hasFeasibilityJumpEnableRestartsin interfaceSatParametersOrBuilder- Returns:
- Whether the feasibilityJumpEnableRestarts field is set.
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getFeasibilityJumpEnableRestarts
public boolean getFeasibilityJumpEnableRestarts()When stagnating, feasibility jump will either restart from a default solution (with some possible randomization), or randomly pertubate the current solution. This parameter selects the first option.
optional bool feasibility_jump_enable_restarts = 250 [default = true];- Specified by:
getFeasibilityJumpEnableRestartsin interfaceSatParametersOrBuilder- Returns:
- The feasibilityJumpEnableRestarts.
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setFeasibilityJumpEnableRestarts
When stagnating, feasibility jump will either restart from a default solution (with some possible randomization), or randomly pertubate the current solution. This parameter selects the first option.
optional bool feasibility_jump_enable_restarts = 250 [default = true];- Parameters:
value- The feasibilityJumpEnableRestarts to set.- Returns:
- This builder for chaining.
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clearFeasibilityJumpEnableRestarts
When stagnating, feasibility jump will either restart from a default solution (with some possible randomization), or randomly pertubate the current solution. This parameter selects the first option.
optional bool feasibility_jump_enable_restarts = 250 [default = true];- Returns:
- This builder for chaining.
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hasFeasibilityJumpMaxExpandedConstraintSize
public boolean hasFeasibilityJumpMaxExpandedConstraintSize()Maximum size of no_overlap or no_overlap_2d constraint for a quadratic expansion. This might look a lot, but by expanding such constraint, we get a linear time evaluation per single variable moves instead of a slow O(n log n) one.
optional int32 feasibility_jump_max_expanded_constraint_size = 264 [default = 500];- Specified by:
hasFeasibilityJumpMaxExpandedConstraintSizein interfaceSatParametersOrBuilder- Returns:
- Whether the feasibilityJumpMaxExpandedConstraintSize field is set.
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getFeasibilityJumpMaxExpandedConstraintSize
public int getFeasibilityJumpMaxExpandedConstraintSize()Maximum size of no_overlap or no_overlap_2d constraint for a quadratic expansion. This might look a lot, but by expanding such constraint, we get a linear time evaluation per single variable moves instead of a slow O(n log n) one.
optional int32 feasibility_jump_max_expanded_constraint_size = 264 [default = 500];- Specified by:
getFeasibilityJumpMaxExpandedConstraintSizein interfaceSatParametersOrBuilder- Returns:
- The feasibilityJumpMaxExpandedConstraintSize.
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setFeasibilityJumpMaxExpandedConstraintSize
Maximum size of no_overlap or no_overlap_2d constraint for a quadratic expansion. This might look a lot, but by expanding such constraint, we get a linear time evaluation per single variable moves instead of a slow O(n log n) one.
optional int32 feasibility_jump_max_expanded_constraint_size = 264 [default = 500];- Parameters:
value- The feasibilityJumpMaxExpandedConstraintSize to set.- Returns:
- This builder for chaining.
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clearFeasibilityJumpMaxExpandedConstraintSize
Maximum size of no_overlap or no_overlap_2d constraint for a quadratic expansion. This might look a lot, but by expanding such constraint, we get a linear time evaluation per single variable moves instead of a slow O(n log n) one.
optional int32 feasibility_jump_max_expanded_constraint_size = 264 [default = 500];- Returns:
- This builder for chaining.
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hasNumViolationLs
public boolean hasNumViolationLs()This will create incomplete subsolvers (that are not LNS subsolvers) that use the feasibility jump code to find improving solution, treating the objective improvement as a hard constraint.
optional int32 num_violation_ls = 244 [default = 0];- Specified by:
hasNumViolationLsin interfaceSatParametersOrBuilder- Returns:
- Whether the numViolationLs field is set.
-
getNumViolationLs
public int getNumViolationLs()This will create incomplete subsolvers (that are not LNS subsolvers) that use the feasibility jump code to find improving solution, treating the objective improvement as a hard constraint.
optional int32 num_violation_ls = 244 [default = 0];- Specified by:
getNumViolationLsin interfaceSatParametersOrBuilder- Returns:
- The numViolationLs.
-
setNumViolationLs
This will create incomplete subsolvers (that are not LNS subsolvers) that use the feasibility jump code to find improving solution, treating the objective improvement as a hard constraint.
optional int32 num_violation_ls = 244 [default = 0];- Parameters:
value- The numViolationLs to set.- Returns:
- This builder for chaining.
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clearNumViolationLs
This will create incomplete subsolvers (that are not LNS subsolvers) that use the feasibility jump code to find improving solution, treating the objective improvement as a hard constraint.
optional int32 num_violation_ls = 244 [default = 0];- Returns:
- This builder for chaining.
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hasViolationLsPerturbationPeriod
public boolean hasViolationLsPerturbationPeriod()How long violation_ls should wait before perturbating a solution.
optional int32 violation_ls_perturbation_period = 249 [default = 100];- Specified by:
hasViolationLsPerturbationPeriodin interfaceSatParametersOrBuilder- Returns:
- Whether the violationLsPerturbationPeriod field is set.
-
getViolationLsPerturbationPeriod
public int getViolationLsPerturbationPeriod()How long violation_ls should wait before perturbating a solution.
optional int32 violation_ls_perturbation_period = 249 [default = 100];- Specified by:
getViolationLsPerturbationPeriodin interfaceSatParametersOrBuilder- Returns:
- The violationLsPerturbationPeriod.
-
setViolationLsPerturbationPeriod
How long violation_ls should wait before perturbating a solution.
optional int32 violation_ls_perturbation_period = 249 [default = 100];- Parameters:
value- The violationLsPerturbationPeriod to set.- Returns:
- This builder for chaining.
-
clearViolationLsPerturbationPeriod
How long violation_ls should wait before perturbating a solution.
optional int32 violation_ls_perturbation_period = 249 [default = 100];- Returns:
- This builder for chaining.
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hasViolationLsCompoundMoveProbability
public boolean hasViolationLsCompoundMoveProbability()Probability of using compound move search each restart. TODO(user): Add reference to paper when published.
optional double violation_ls_compound_move_probability = 259 [default = 0.5];- Specified by:
hasViolationLsCompoundMoveProbabilityin interfaceSatParametersOrBuilder- Returns:
- Whether the violationLsCompoundMoveProbability field is set.
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getViolationLsCompoundMoveProbability
public double getViolationLsCompoundMoveProbability()Probability of using compound move search each restart. TODO(user): Add reference to paper when published.
optional double violation_ls_compound_move_probability = 259 [default = 0.5];- Specified by:
getViolationLsCompoundMoveProbabilityin interfaceSatParametersOrBuilder- Returns:
- The violationLsCompoundMoveProbability.
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setViolationLsCompoundMoveProbability
Probability of using compound move search each restart. TODO(user): Add reference to paper when published.
optional double violation_ls_compound_move_probability = 259 [default = 0.5];- Parameters:
value- The violationLsCompoundMoveProbability to set.- Returns:
- This builder for chaining.
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clearViolationLsCompoundMoveProbability
Probability of using compound move search each restart. TODO(user): Add reference to paper when published.
optional double violation_ls_compound_move_probability = 259 [default = 0.5];- Returns:
- This builder for chaining.
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hasEnumerateAllSolutions
public boolean hasEnumerateAllSolutions()Whether we enumerate all solutions of a problem without objective. WARNING: - This can be used with num_workers > 1 but then each solutions can be found more than once, so it is up to the client to deduplicate them. - If keep_all_feasible_solutions_in_presolve is unset, we will set it to true as otherwise, many feasible solution can just be removed by the presolve. It is still possible to manually set this to false if one only wants to enumerate all solutions of the presolved model.
optional bool enumerate_all_solutions = 87 [default = false];- Specified by:
hasEnumerateAllSolutionsin interfaceSatParametersOrBuilder- Returns:
- Whether the enumerateAllSolutions field is set.
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getEnumerateAllSolutions
public boolean getEnumerateAllSolutions()Whether we enumerate all solutions of a problem without objective. WARNING: - This can be used with num_workers > 1 but then each solutions can be found more than once, so it is up to the client to deduplicate them. - If keep_all_feasible_solutions_in_presolve is unset, we will set it to true as otherwise, many feasible solution can just be removed by the presolve. It is still possible to manually set this to false if one only wants to enumerate all solutions of the presolved model.
optional bool enumerate_all_solutions = 87 [default = false];- Specified by:
getEnumerateAllSolutionsin interfaceSatParametersOrBuilder- Returns:
- The enumerateAllSolutions.
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setEnumerateAllSolutions
Whether we enumerate all solutions of a problem without objective. WARNING: - This can be used with num_workers > 1 but then each solutions can be found more than once, so it is up to the client to deduplicate them. - If keep_all_feasible_solutions_in_presolve is unset, we will set it to true as otherwise, many feasible solution can just be removed by the presolve. It is still possible to manually set this to false if one only wants to enumerate all solutions of the presolved model.
optional bool enumerate_all_solutions = 87 [default = false];- Parameters:
value- The enumerateAllSolutions to set.- Returns:
- This builder for chaining.
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clearEnumerateAllSolutions
Whether we enumerate all solutions of a problem without objective. WARNING: - This can be used with num_workers > 1 but then each solutions can be found more than once, so it is up to the client to deduplicate them. - If keep_all_feasible_solutions_in_presolve is unset, we will set it to true as otherwise, many feasible solution can just be removed by the presolve. It is still possible to manually set this to false if one only wants to enumerate all solutions of the presolved model.
optional bool enumerate_all_solutions = 87 [default = false];- Returns:
- This builder for chaining.
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hasKeepAllFeasibleSolutionsInPresolve
public boolean hasKeepAllFeasibleSolutionsInPresolve()If true, we disable the presolve reductions that remove feasible solutions from the search space. Such solution are usually dominated by a "better" solution that is kept, but depending on the situation, we might want to keep all solutions. A trivial example is when a variable is unused. If this is true, then the presolve will not fix it to an arbitrary value and it will stay in the search space.
optional bool keep_all_feasible_solutions_in_presolve = 173 [default = false];- Specified by:
hasKeepAllFeasibleSolutionsInPresolvein interfaceSatParametersOrBuilder- Returns:
- Whether the keepAllFeasibleSolutionsInPresolve field is set.
-
getKeepAllFeasibleSolutionsInPresolve
public boolean getKeepAllFeasibleSolutionsInPresolve()If true, we disable the presolve reductions that remove feasible solutions from the search space. Such solution are usually dominated by a "better" solution that is kept, but depending on the situation, we might want to keep all solutions. A trivial example is when a variable is unused. If this is true, then the presolve will not fix it to an arbitrary value and it will stay in the search space.
optional bool keep_all_feasible_solutions_in_presolve = 173 [default = false];- Specified by:
getKeepAllFeasibleSolutionsInPresolvein interfaceSatParametersOrBuilder- Returns:
- The keepAllFeasibleSolutionsInPresolve.
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setKeepAllFeasibleSolutionsInPresolve
If true, we disable the presolve reductions that remove feasible solutions from the search space. Such solution are usually dominated by a "better" solution that is kept, but depending on the situation, we might want to keep all solutions. A trivial example is when a variable is unused. If this is true, then the presolve will not fix it to an arbitrary value and it will stay in the search space.
optional bool keep_all_feasible_solutions_in_presolve = 173 [default = false];- Parameters:
value- The keepAllFeasibleSolutionsInPresolve to set.- Returns:
- This builder for chaining.
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clearKeepAllFeasibleSolutionsInPresolve
If true, we disable the presolve reductions that remove feasible solutions from the search space. Such solution are usually dominated by a "better" solution that is kept, but depending on the situation, we might want to keep all solutions. A trivial example is when a variable is unused. If this is true, then the presolve will not fix it to an arbitrary value and it will stay in the search space.
optional bool keep_all_feasible_solutions_in_presolve = 173 [default = false];- Returns:
- This builder for chaining.
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hasFillTightenedDomainsInResponse
public boolean hasFillTightenedDomainsInResponse()If true, add information about the derived variable domains to the CpSolverResponse. It is an option because it makes the response slighly bigger and there is a bit more work involved during the postsolve to construct it, but it should still have a low overhead. See the tightened_variables field in CpSolverResponse for more details.
optional bool fill_tightened_domains_in_response = 132 [default = false];- Specified by:
hasFillTightenedDomainsInResponsein interfaceSatParametersOrBuilder- Returns:
- Whether the fillTightenedDomainsInResponse field is set.
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getFillTightenedDomainsInResponse
public boolean getFillTightenedDomainsInResponse()If true, add information about the derived variable domains to the CpSolverResponse. It is an option because it makes the response slighly bigger and there is a bit more work involved during the postsolve to construct it, but it should still have a low overhead. See the tightened_variables field in CpSolverResponse for more details.
optional bool fill_tightened_domains_in_response = 132 [default = false];- Specified by:
getFillTightenedDomainsInResponsein interfaceSatParametersOrBuilder- Returns:
- The fillTightenedDomainsInResponse.
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setFillTightenedDomainsInResponse
If true, add information about the derived variable domains to the CpSolverResponse. It is an option because it makes the response slighly bigger and there is a bit more work involved during the postsolve to construct it, but it should still have a low overhead. See the tightened_variables field in CpSolverResponse for more details.
optional bool fill_tightened_domains_in_response = 132 [default = false];- Parameters:
value- The fillTightenedDomainsInResponse to set.- Returns:
- This builder for chaining.
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clearFillTightenedDomainsInResponse
If true, add information about the derived variable domains to the CpSolverResponse. It is an option because it makes the response slighly bigger and there is a bit more work involved during the postsolve to construct it, but it should still have a low overhead. See the tightened_variables field in CpSolverResponse for more details.
optional bool fill_tightened_domains_in_response = 132 [default = false];- Returns:
- This builder for chaining.
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hasFillAdditionalSolutionsInResponse
public boolean hasFillAdditionalSolutionsInResponse()If true, the final response addition_solutions field will be filled with all solutions from our solutions pool. Note that if both this field and enumerate_all_solutions is true, we will copy to the pool all of the solution found. So if solution_pool_size is big enough, you can get all solutions this way instead of using the solution callback. Note that this only affect the "final" solution, not the one passed to the solution callbacks.
optional bool fill_additional_solutions_in_response = 194 [default = false];- Specified by:
hasFillAdditionalSolutionsInResponsein interfaceSatParametersOrBuilder- Returns:
- Whether the fillAdditionalSolutionsInResponse field is set.
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getFillAdditionalSolutionsInResponse
public boolean getFillAdditionalSolutionsInResponse()If true, the final response addition_solutions field will be filled with all solutions from our solutions pool. Note that if both this field and enumerate_all_solutions is true, we will copy to the pool all of the solution found. So if solution_pool_size is big enough, you can get all solutions this way instead of using the solution callback. Note that this only affect the "final" solution, not the one passed to the solution callbacks.
optional bool fill_additional_solutions_in_response = 194 [default = false];- Specified by:
getFillAdditionalSolutionsInResponsein interfaceSatParametersOrBuilder- Returns:
- The fillAdditionalSolutionsInResponse.
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setFillAdditionalSolutionsInResponse
If true, the final response addition_solutions field will be filled with all solutions from our solutions pool. Note that if both this field and enumerate_all_solutions is true, we will copy to the pool all of the solution found. So if solution_pool_size is big enough, you can get all solutions this way instead of using the solution callback. Note that this only affect the "final" solution, not the one passed to the solution callbacks.
optional bool fill_additional_solutions_in_response = 194 [default = false];- Parameters:
value- The fillAdditionalSolutionsInResponse to set.- Returns:
- This builder for chaining.
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clearFillAdditionalSolutionsInResponse
If true, the final response addition_solutions field will be filled with all solutions from our solutions pool. Note that if both this field and enumerate_all_solutions is true, we will copy to the pool all of the solution found. So if solution_pool_size is big enough, you can get all solutions this way instead of using the solution callback. Note that this only affect the "final" solution, not the one passed to the solution callbacks.
optional bool fill_additional_solutions_in_response = 194 [default = false];- Returns:
- This builder for chaining.
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hasInstantiateAllVariables
public boolean hasInstantiateAllVariables()If true, the solver will add a default integer branching strategy to the already defined search strategy. If not, some variable might still not be fixed at the end of the search. For now we assume these variable can just be set to their lower bound.
optional bool instantiate_all_variables = 106 [default = true];- Specified by:
hasInstantiateAllVariablesin interfaceSatParametersOrBuilder- Returns:
- Whether the instantiateAllVariables field is set.
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getInstantiateAllVariables
public boolean getInstantiateAllVariables()If true, the solver will add a default integer branching strategy to the already defined search strategy. If not, some variable might still not be fixed at the end of the search. For now we assume these variable can just be set to their lower bound.
optional bool instantiate_all_variables = 106 [default = true];- Specified by:
getInstantiateAllVariablesin interfaceSatParametersOrBuilder- Returns:
- The instantiateAllVariables.
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setInstantiateAllVariables
If true, the solver will add a default integer branching strategy to the already defined search strategy. If not, some variable might still not be fixed at the end of the search. For now we assume these variable can just be set to their lower bound.
optional bool instantiate_all_variables = 106 [default = true];- Parameters:
value- The instantiateAllVariables to set.- Returns:
- This builder for chaining.
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clearInstantiateAllVariables
If true, the solver will add a default integer branching strategy to the already defined search strategy. If not, some variable might still not be fixed at the end of the search. For now we assume these variable can just be set to their lower bound.
optional bool instantiate_all_variables = 106 [default = true];- Returns:
- This builder for chaining.
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hasAutoDetectGreaterThanAtLeastOneOf
public boolean hasAutoDetectGreaterThanAtLeastOneOf()If true, then the precedences propagator try to detect for each variable if it has a set of "optional incoming arc" for which at least one of them is present. This is usually useful to have but can be slow on model with a lot of precedence.
optional bool auto_detect_greater_than_at_least_one_of = 95 [default = true];- Specified by:
hasAutoDetectGreaterThanAtLeastOneOfin interfaceSatParametersOrBuilder- Returns:
- Whether the autoDetectGreaterThanAtLeastOneOf field is set.
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getAutoDetectGreaterThanAtLeastOneOf
public boolean getAutoDetectGreaterThanAtLeastOneOf()If true, then the precedences propagator try to detect for each variable if it has a set of "optional incoming arc" for which at least one of them is present. This is usually useful to have but can be slow on model with a lot of precedence.
optional bool auto_detect_greater_than_at_least_one_of = 95 [default = true];- Specified by:
getAutoDetectGreaterThanAtLeastOneOfin interfaceSatParametersOrBuilder- Returns:
- The autoDetectGreaterThanAtLeastOneOf.
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setAutoDetectGreaterThanAtLeastOneOf
If true, then the precedences propagator try to detect for each variable if it has a set of "optional incoming arc" for which at least one of them is present. This is usually useful to have but can be slow on model with a lot of precedence.
optional bool auto_detect_greater_than_at_least_one_of = 95 [default = true];- Parameters:
value- The autoDetectGreaterThanAtLeastOneOf to set.- Returns:
- This builder for chaining.
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clearAutoDetectGreaterThanAtLeastOneOf
If true, then the precedences propagator try to detect for each variable if it has a set of "optional incoming arc" for which at least one of them is present. This is usually useful to have but can be slow on model with a lot of precedence.
optional bool auto_detect_greater_than_at_least_one_of = 95 [default = true];- Returns:
- This builder for chaining.
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hasStopAfterFirstSolution
public boolean hasStopAfterFirstSolution()For an optimization problem, stop the solver as soon as we have a solution.
optional bool stop_after_first_solution = 98 [default = false];- Specified by:
hasStopAfterFirstSolutionin interfaceSatParametersOrBuilder- Returns:
- Whether the stopAfterFirstSolution field is set.
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getStopAfterFirstSolution
public boolean getStopAfterFirstSolution()For an optimization problem, stop the solver as soon as we have a solution.
optional bool stop_after_first_solution = 98 [default = false];- Specified by:
getStopAfterFirstSolutionin interfaceSatParametersOrBuilder- Returns:
- The stopAfterFirstSolution.
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setStopAfterFirstSolution
For an optimization problem, stop the solver as soon as we have a solution.
optional bool stop_after_first_solution = 98 [default = false];- Parameters:
value- The stopAfterFirstSolution to set.- Returns:
- This builder for chaining.
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clearStopAfterFirstSolution
For an optimization problem, stop the solver as soon as we have a solution.
optional bool stop_after_first_solution = 98 [default = false];- Returns:
- This builder for chaining.
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hasStopAfterPresolve
public boolean hasStopAfterPresolve()Mainly used when improving the presolver. When true, stops the solver after the presolve is complete (or after loading and root level propagation).
optional bool stop_after_presolve = 149 [default = false];- Specified by:
hasStopAfterPresolvein interfaceSatParametersOrBuilder- Returns:
- Whether the stopAfterPresolve field is set.
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getStopAfterPresolve
public boolean getStopAfterPresolve()Mainly used when improving the presolver. When true, stops the solver after the presolve is complete (or after loading and root level propagation).
optional bool stop_after_presolve = 149 [default = false];- Specified by:
getStopAfterPresolvein interfaceSatParametersOrBuilder- Returns:
- The stopAfterPresolve.
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setStopAfterPresolve
Mainly used when improving the presolver. When true, stops the solver after the presolve is complete (or after loading and root level propagation).
optional bool stop_after_presolve = 149 [default = false];- Parameters:
value- The stopAfterPresolve to set.- Returns:
- This builder for chaining.
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clearStopAfterPresolve
Mainly used when improving the presolver. When true, stops the solver after the presolve is complete (or after loading and root level propagation).
optional bool stop_after_presolve = 149 [default = false];- Returns:
- This builder for chaining.
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hasStopAfterRootPropagation
public boolean hasStopAfterRootPropagation()optional bool stop_after_root_propagation = 252 [default = false];- Specified by:
hasStopAfterRootPropagationin interfaceSatParametersOrBuilder- Returns:
- Whether the stopAfterRootPropagation field is set.
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getStopAfterRootPropagation
public boolean getStopAfterRootPropagation()optional bool stop_after_root_propagation = 252 [default = false];- Specified by:
getStopAfterRootPropagationin interfaceSatParametersOrBuilder- Returns:
- The stopAfterRootPropagation.
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setStopAfterRootPropagation
optional bool stop_after_root_propagation = 252 [default = false];- Parameters:
value- The stopAfterRootPropagation to set.- Returns:
- This builder for chaining.
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clearStopAfterRootPropagation
optional bool stop_after_root_propagation = 252 [default = false];- Returns:
- This builder for chaining.
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hasLnsInitialDifficulty
public boolean hasLnsInitialDifficulty()Initial parameters for neighborhood generation.
optional double lns_initial_difficulty = 307 [default = 0.5];- Specified by:
hasLnsInitialDifficultyin interfaceSatParametersOrBuilder- Returns:
- Whether the lnsInitialDifficulty field is set.
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getLnsInitialDifficulty
public double getLnsInitialDifficulty()Initial parameters for neighborhood generation.
optional double lns_initial_difficulty = 307 [default = 0.5];- Specified by:
getLnsInitialDifficultyin interfaceSatParametersOrBuilder- Returns:
- The lnsInitialDifficulty.
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setLnsInitialDifficulty
Initial parameters for neighborhood generation.
optional double lns_initial_difficulty = 307 [default = 0.5];- Parameters:
value- The lnsInitialDifficulty to set.- Returns:
- This builder for chaining.
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clearLnsInitialDifficulty
Initial parameters for neighborhood generation.
optional double lns_initial_difficulty = 307 [default = 0.5];- Returns:
- This builder for chaining.
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hasLnsInitialDeterministicLimit
public boolean hasLnsInitialDeterministicLimit()optional double lns_initial_deterministic_limit = 308 [default = 0.1];- Specified by:
hasLnsInitialDeterministicLimitin interfaceSatParametersOrBuilder- Returns:
- Whether the lnsInitialDeterministicLimit field is set.
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getLnsInitialDeterministicLimit
public double getLnsInitialDeterministicLimit()optional double lns_initial_deterministic_limit = 308 [default = 0.1];- Specified by:
getLnsInitialDeterministicLimitin interfaceSatParametersOrBuilder- Returns:
- The lnsInitialDeterministicLimit.
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setLnsInitialDeterministicLimit
optional double lns_initial_deterministic_limit = 308 [default = 0.1];- Parameters:
value- The lnsInitialDeterministicLimit to set.- Returns:
- This builder for chaining.
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clearLnsInitialDeterministicLimit
optional double lns_initial_deterministic_limit = 308 [default = 0.1];- Returns:
- This builder for chaining.
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hasUseLns
public boolean hasUseLns()Testing parameters used to disable all lns workers.
optional bool use_lns = 283 [default = true];- Specified by:
hasUseLnsin interfaceSatParametersOrBuilder- Returns:
- Whether the useLns field is set.
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getUseLns
public boolean getUseLns()Testing parameters used to disable all lns workers.
optional bool use_lns = 283 [default = true];- Specified by:
getUseLnsin interfaceSatParametersOrBuilder- Returns:
- The useLns.
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setUseLns
Testing parameters used to disable all lns workers.
optional bool use_lns = 283 [default = true];- Parameters:
value- The useLns to set.- Returns:
- This builder for chaining.
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clearUseLns
Testing parameters used to disable all lns workers.
optional bool use_lns = 283 [default = true];- Returns:
- This builder for chaining.
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hasUseLnsOnly
public boolean hasUseLnsOnly()Experimental parameters to disable everything but lns.
optional bool use_lns_only = 101 [default = false];- Specified by:
hasUseLnsOnlyin interfaceSatParametersOrBuilder- Returns:
- Whether the useLnsOnly field is set.
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getUseLnsOnly
public boolean getUseLnsOnly()Experimental parameters to disable everything but lns.
optional bool use_lns_only = 101 [default = false];- Specified by:
getUseLnsOnlyin interfaceSatParametersOrBuilder- Returns:
- The useLnsOnly.
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setUseLnsOnly
Experimental parameters to disable everything but lns.
optional bool use_lns_only = 101 [default = false];- Parameters:
value- The useLnsOnly to set.- Returns:
- This builder for chaining.
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clearUseLnsOnly
Experimental parameters to disable everything but lns.
optional bool use_lns_only = 101 [default = false];- Returns:
- This builder for chaining.
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hasSolutionPoolSize
public boolean hasSolutionPoolSize()Size of the top-n different solutions kept by the solver. This parameter must be > 0. Currently, having this larger than one mainly impact the "base" solution chosen for a LNS/LS fragment.
optional int32 solution_pool_size = 193 [default = 3];- Specified by:
hasSolutionPoolSizein interfaceSatParametersOrBuilder- Returns:
- Whether the solutionPoolSize field is set.
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getSolutionPoolSize
public int getSolutionPoolSize()Size of the top-n different solutions kept by the solver. This parameter must be > 0. Currently, having this larger than one mainly impact the "base" solution chosen for a LNS/LS fragment.
optional int32 solution_pool_size = 193 [default = 3];- Specified by:
getSolutionPoolSizein interfaceSatParametersOrBuilder- Returns:
- The solutionPoolSize.
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setSolutionPoolSize
Size of the top-n different solutions kept by the solver. This parameter must be > 0. Currently, having this larger than one mainly impact the "base" solution chosen for a LNS/LS fragment.
optional int32 solution_pool_size = 193 [default = 3];- Parameters:
value- The solutionPoolSize to set.- Returns:
- This builder for chaining.
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clearSolutionPoolSize
Size of the top-n different solutions kept by the solver. This parameter must be > 0. Currently, having this larger than one mainly impact the "base" solution chosen for a LNS/LS fragment.
optional int32 solution_pool_size = 193 [default = 3];- Returns:
- This builder for chaining.
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hasSolutionPoolDiversityLimit
public boolean hasSolutionPoolDiversityLimit()If solution_pool_size is <= this, we will use DP to keep a "diverse" set of solutions (the one further apart via hamming distance) in the pool. Setting this to large value might be slow, especially if your solution are large.
optional int32 solution_pool_diversity_limit = 329 [default = 10];- Specified by:
hasSolutionPoolDiversityLimitin interfaceSatParametersOrBuilder- Returns:
- Whether the solutionPoolDiversityLimit field is set.
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getSolutionPoolDiversityLimit
public int getSolutionPoolDiversityLimit()If solution_pool_size is <= this, we will use DP to keep a "diverse" set of solutions (the one further apart via hamming distance) in the pool. Setting this to large value might be slow, especially if your solution are large.
optional int32 solution_pool_diversity_limit = 329 [default = 10];- Specified by:
getSolutionPoolDiversityLimitin interfaceSatParametersOrBuilder- Returns:
- The solutionPoolDiversityLimit.
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setSolutionPoolDiversityLimit
If solution_pool_size is <= this, we will use DP to keep a "diverse" set of solutions (the one further apart via hamming distance) in the pool. Setting this to large value might be slow, especially if your solution are large.
optional int32 solution_pool_diversity_limit = 329 [default = 10];- Parameters:
value- The solutionPoolDiversityLimit to set.- Returns:
- This builder for chaining.
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clearSolutionPoolDiversityLimit
If solution_pool_size is <= this, we will use DP to keep a "diverse" set of solutions (the one further apart via hamming distance) in the pool. Setting this to large value might be slow, especially if your solution are large.
optional int32 solution_pool_diversity_limit = 329 [default = 10];- Returns:
- This builder for chaining.
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hasAlternativePoolSize
public boolean hasAlternativePoolSize()In order to not get stuck in local optima, when this is non-zero, we try to also work on "older" solutions with a worse objective value so we get a chance to follow a different LS/LNS trajectory.
optional int32 alternative_pool_size = 325 [default = 1];- Specified by:
hasAlternativePoolSizein interfaceSatParametersOrBuilder- Returns:
- Whether the alternativePoolSize field is set.
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getAlternativePoolSize
public int getAlternativePoolSize()In order to not get stuck in local optima, when this is non-zero, we try to also work on "older" solutions with a worse objective value so we get a chance to follow a different LS/LNS trajectory.
optional int32 alternative_pool_size = 325 [default = 1];- Specified by:
getAlternativePoolSizein interfaceSatParametersOrBuilder- Returns:
- The alternativePoolSize.
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setAlternativePoolSize
In order to not get stuck in local optima, when this is non-zero, we try to also work on "older" solutions with a worse objective value so we get a chance to follow a different LS/LNS trajectory.
optional int32 alternative_pool_size = 325 [default = 1];- Parameters:
value- The alternativePoolSize to set.- Returns:
- This builder for chaining.
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clearAlternativePoolSize
In order to not get stuck in local optima, when this is non-zero, we try to also work on "older" solutions with a worse objective value so we get a chance to follow a different LS/LNS trajectory.
optional int32 alternative_pool_size = 325 [default = 1];- Returns:
- This builder for chaining.
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hasUseRinsLns
public boolean hasUseRinsLns()Turns on relaxation induced neighborhood generator.
optional bool use_rins_lns = 129 [default = true];- Specified by:
hasUseRinsLnsin interfaceSatParametersOrBuilder- Returns:
- Whether the useRinsLns field is set.
-
getUseRinsLns
public boolean getUseRinsLns()Turns on relaxation induced neighborhood generator.
optional bool use_rins_lns = 129 [default = true];- Specified by:
getUseRinsLnsin interfaceSatParametersOrBuilder- Returns:
- The useRinsLns.
-
setUseRinsLns
Turns on relaxation induced neighborhood generator.
optional bool use_rins_lns = 129 [default = true];- Parameters:
value- The useRinsLns to set.- Returns:
- This builder for chaining.
-
clearUseRinsLns
Turns on relaxation induced neighborhood generator.
optional bool use_rins_lns = 129 [default = true];- Returns:
- This builder for chaining.
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hasUseFeasibilityPump
public boolean hasUseFeasibilityPump()Adds a feasibility pump subsolver along with lns subsolvers.
optional bool use_feasibility_pump = 164 [default = true];- Specified by:
hasUseFeasibilityPumpin interfaceSatParametersOrBuilder- Returns:
- Whether the useFeasibilityPump field is set.
-
getUseFeasibilityPump
public boolean getUseFeasibilityPump()Adds a feasibility pump subsolver along with lns subsolvers.
optional bool use_feasibility_pump = 164 [default = true];- Specified by:
getUseFeasibilityPumpin interfaceSatParametersOrBuilder- Returns:
- The useFeasibilityPump.
-
setUseFeasibilityPump
Adds a feasibility pump subsolver along with lns subsolvers.
optional bool use_feasibility_pump = 164 [default = true];- Parameters:
value- The useFeasibilityPump to set.- Returns:
- This builder for chaining.
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clearUseFeasibilityPump
Adds a feasibility pump subsolver along with lns subsolvers.
optional bool use_feasibility_pump = 164 [default = true];- Returns:
- This builder for chaining.
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hasUseLbRelaxLns
public boolean hasUseLbRelaxLns()Turns on neighborhood generator based on local branching LP. Based on Huang et al., "Local Branching Relaxation Heuristics for Integer Linear Programs", 2023.
optional bool use_lb_relax_lns = 255 [default = true];- Specified by:
hasUseLbRelaxLnsin interfaceSatParametersOrBuilder- Returns:
- Whether the useLbRelaxLns field is set.
-
getUseLbRelaxLns
public boolean getUseLbRelaxLns()Turns on neighborhood generator based on local branching LP. Based on Huang et al., "Local Branching Relaxation Heuristics for Integer Linear Programs", 2023.
optional bool use_lb_relax_lns = 255 [default = true];- Specified by:
getUseLbRelaxLnsin interfaceSatParametersOrBuilder- Returns:
- The useLbRelaxLns.
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setUseLbRelaxLns
Turns on neighborhood generator based on local branching LP. Based on Huang et al., "Local Branching Relaxation Heuristics for Integer Linear Programs", 2023.
optional bool use_lb_relax_lns = 255 [default = true];- Parameters:
value- The useLbRelaxLns to set.- Returns:
- This builder for chaining.
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clearUseLbRelaxLns
Turns on neighborhood generator based on local branching LP. Based on Huang et al., "Local Branching Relaxation Heuristics for Integer Linear Programs", 2023.
optional bool use_lb_relax_lns = 255 [default = true];- Returns:
- This builder for chaining.
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hasLbRelaxNumWorkersThreshold
public boolean hasLbRelaxNumWorkersThreshold()Only use lb-relax if we have at least that many workers.
optional int32 lb_relax_num_workers_threshold = 296 [default = 16];- Specified by:
hasLbRelaxNumWorkersThresholdin interfaceSatParametersOrBuilder- Returns:
- Whether the lbRelaxNumWorkersThreshold field is set.
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getLbRelaxNumWorkersThreshold
public int getLbRelaxNumWorkersThreshold()Only use lb-relax if we have at least that many workers.
optional int32 lb_relax_num_workers_threshold = 296 [default = 16];- Specified by:
getLbRelaxNumWorkersThresholdin interfaceSatParametersOrBuilder- Returns:
- The lbRelaxNumWorkersThreshold.
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setLbRelaxNumWorkersThreshold
Only use lb-relax if we have at least that many workers.
optional int32 lb_relax_num_workers_threshold = 296 [default = 16];- Parameters:
value- The lbRelaxNumWorkersThreshold to set.- Returns:
- This builder for chaining.
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clearLbRelaxNumWorkersThreshold
Only use lb-relax if we have at least that many workers.
optional int32 lb_relax_num_workers_threshold = 296 [default = 16];- Returns:
- This builder for chaining.
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hasFpRounding
public boolean hasFpRounding()optional .operations_research.sat.SatParameters.FPRoundingMethod fp_rounding = 165 [default = PROPAGATION_ASSISTED];- Specified by:
hasFpRoundingin interfaceSatParametersOrBuilder- Returns:
- Whether the fpRounding field is set.
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getFpRounding
optional .operations_research.sat.SatParameters.FPRoundingMethod fp_rounding = 165 [default = PROPAGATION_ASSISTED];- Specified by:
getFpRoundingin interfaceSatParametersOrBuilder- Returns:
- The fpRounding.
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setFpRounding
optional .operations_research.sat.SatParameters.FPRoundingMethod fp_rounding = 165 [default = PROPAGATION_ASSISTED];- Parameters:
value- The fpRounding to set.- Returns:
- This builder for chaining.
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clearFpRounding
optional .operations_research.sat.SatParameters.FPRoundingMethod fp_rounding = 165 [default = PROPAGATION_ASSISTED];- Returns:
- This builder for chaining.
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hasDiversifyLnsParams
public boolean hasDiversifyLnsParams()If true, registers more lns subsolvers with different parameters.
optional bool diversify_lns_params = 137 [default = false];- Specified by:
hasDiversifyLnsParamsin interfaceSatParametersOrBuilder- Returns:
- Whether the diversifyLnsParams field is set.
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getDiversifyLnsParams
public boolean getDiversifyLnsParams()If true, registers more lns subsolvers with different parameters.
optional bool diversify_lns_params = 137 [default = false];- Specified by:
getDiversifyLnsParamsin interfaceSatParametersOrBuilder- Returns:
- The diversifyLnsParams.
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setDiversifyLnsParams
If true, registers more lns subsolvers with different parameters.
optional bool diversify_lns_params = 137 [default = false];- Parameters:
value- The diversifyLnsParams to set.- Returns:
- This builder for chaining.
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clearDiversifyLnsParams
If true, registers more lns subsolvers with different parameters.
optional bool diversify_lns_params = 137 [default = false];- Returns:
- This builder for chaining.
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hasRandomizeSearch
public boolean hasRandomizeSearch()Randomize fixed search.
optional bool randomize_search = 103 [default = false];- Specified by:
hasRandomizeSearchin interfaceSatParametersOrBuilder- Returns:
- Whether the randomizeSearch field is set.
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getRandomizeSearch
public boolean getRandomizeSearch()Randomize fixed search.
optional bool randomize_search = 103 [default = false];- Specified by:
getRandomizeSearchin interfaceSatParametersOrBuilder- Returns:
- The randomizeSearch.
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setRandomizeSearch
Randomize fixed search.
optional bool randomize_search = 103 [default = false];- Parameters:
value- The randomizeSearch to set.- Returns:
- This builder for chaining.
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clearRandomizeSearch
Randomize fixed search.
optional bool randomize_search = 103 [default = false];- Returns:
- This builder for chaining.
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hasSearchRandomVariablePoolSize
public boolean hasSearchRandomVariablePoolSize()Search randomization will collect the top 'search_random_variable_pool_size' valued variables, and pick one randomly. The value of the variable is specific to each strategy.
optional int64 search_random_variable_pool_size = 104 [default = 0];- Specified by:
hasSearchRandomVariablePoolSizein interfaceSatParametersOrBuilder- Returns:
- Whether the searchRandomVariablePoolSize field is set.
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getSearchRandomVariablePoolSize
public long getSearchRandomVariablePoolSize()Search randomization will collect the top 'search_random_variable_pool_size' valued variables, and pick one randomly. The value of the variable is specific to each strategy.
optional int64 search_random_variable_pool_size = 104 [default = 0];- Specified by:
getSearchRandomVariablePoolSizein interfaceSatParametersOrBuilder- Returns:
- The searchRandomVariablePoolSize.
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setSearchRandomVariablePoolSize
Search randomization will collect the top 'search_random_variable_pool_size' valued variables, and pick one randomly. The value of the variable is specific to each strategy.
optional int64 search_random_variable_pool_size = 104 [default = 0];- Parameters:
value- The searchRandomVariablePoolSize to set.- Returns:
- This builder for chaining.
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clearSearchRandomVariablePoolSize
Search randomization will collect the top 'search_random_variable_pool_size' valued variables, and pick one randomly. The value of the variable is specific to each strategy.
optional int64 search_random_variable_pool_size = 104 [default = 0];- Returns:
- This builder for chaining.
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hasPushAllTasksTowardStart
public boolean hasPushAllTasksTowardStart()Experimental code: specify if the objective pushes all tasks toward the start of the schedule.
optional bool push_all_tasks_toward_start = 262 [default = false];- Specified by:
hasPushAllTasksTowardStartin interfaceSatParametersOrBuilder- Returns:
- Whether the pushAllTasksTowardStart field is set.
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getPushAllTasksTowardStart
public boolean getPushAllTasksTowardStart()Experimental code: specify if the objective pushes all tasks toward the start of the schedule.
optional bool push_all_tasks_toward_start = 262 [default = false];- Specified by:
getPushAllTasksTowardStartin interfaceSatParametersOrBuilder- Returns:
- The pushAllTasksTowardStart.
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setPushAllTasksTowardStart
Experimental code: specify if the objective pushes all tasks toward the start of the schedule.
optional bool push_all_tasks_toward_start = 262 [default = false];- Parameters:
value- The pushAllTasksTowardStart to set.- Returns:
- This builder for chaining.
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clearPushAllTasksTowardStart
Experimental code: specify if the objective pushes all tasks toward the start of the schedule.
optional bool push_all_tasks_toward_start = 262 [default = false];- Returns:
- This builder for chaining.
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hasUseOptionalVariables
public boolean hasUseOptionalVariables()If true, we automatically detect variables whose constraint are always enforced by the same literal and we mark them as optional. This allows to propagate them as if they were present in some situation. TODO(user): This is experimental and seems to lead to wrong optimal in some situation. It should however gives correct solutions. Fix.
optional bool use_optional_variables = 108 [default = false];- Specified by:
hasUseOptionalVariablesin interfaceSatParametersOrBuilder- Returns:
- Whether the useOptionalVariables field is set.
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getUseOptionalVariables
public boolean getUseOptionalVariables()If true, we automatically detect variables whose constraint are always enforced by the same literal and we mark them as optional. This allows to propagate them as if they were present in some situation. TODO(user): This is experimental and seems to lead to wrong optimal in some situation. It should however gives correct solutions. Fix.
optional bool use_optional_variables = 108 [default = false];- Specified by:
getUseOptionalVariablesin interfaceSatParametersOrBuilder- Returns:
- The useOptionalVariables.
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setUseOptionalVariables
If true, we automatically detect variables whose constraint are always enforced by the same literal and we mark them as optional. This allows to propagate them as if they were present in some situation. TODO(user): This is experimental and seems to lead to wrong optimal in some situation. It should however gives correct solutions. Fix.
optional bool use_optional_variables = 108 [default = false];- Parameters:
value- The useOptionalVariables to set.- Returns:
- This builder for chaining.
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clearUseOptionalVariables
If true, we automatically detect variables whose constraint are always enforced by the same literal and we mark them as optional. This allows to propagate them as if they were present in some situation. TODO(user): This is experimental and seems to lead to wrong optimal in some situation. It should however gives correct solutions. Fix.
optional bool use_optional_variables = 108 [default = false];- Returns:
- This builder for chaining.
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hasUseExactLpReason
public boolean hasUseExactLpReason()The solver usually exploit the LP relaxation of a model. If this option is true, then whatever is infered by the LP will be used like an heuristic to compute EXACT propagation on the IP. So with this option, there is no numerical imprecision issues.
optional bool use_exact_lp_reason = 109 [default = true];- Specified by:
hasUseExactLpReasonin interfaceSatParametersOrBuilder- Returns:
- Whether the useExactLpReason field is set.
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getUseExactLpReason
public boolean getUseExactLpReason()The solver usually exploit the LP relaxation of a model. If this option is true, then whatever is infered by the LP will be used like an heuristic to compute EXACT propagation on the IP. So with this option, there is no numerical imprecision issues.
optional bool use_exact_lp_reason = 109 [default = true];- Specified by:
getUseExactLpReasonin interfaceSatParametersOrBuilder- Returns:
- The useExactLpReason.
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setUseExactLpReason
The solver usually exploit the LP relaxation of a model. If this option is true, then whatever is infered by the LP will be used like an heuristic to compute EXACT propagation on the IP. So with this option, there is no numerical imprecision issues.
optional bool use_exact_lp_reason = 109 [default = true];- Parameters:
value- The useExactLpReason to set.- Returns:
- This builder for chaining.
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clearUseExactLpReason
The solver usually exploit the LP relaxation of a model. If this option is true, then whatever is infered by the LP will be used like an heuristic to compute EXACT propagation on the IP. So with this option, there is no numerical imprecision issues.
optional bool use_exact_lp_reason = 109 [default = true];- Returns:
- This builder for chaining.
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hasUseCombinedNoOverlap
public boolean hasUseCombinedNoOverlap()This can be beneficial if there is a lot of no-overlap constraints but a relatively low number of different intervals in the problem. Like 1000 intervals, but 1M intervals in the no-overlap constraints covering them.
optional bool use_combined_no_overlap = 133 [default = false];- Specified by:
hasUseCombinedNoOverlapin interfaceSatParametersOrBuilder- Returns:
- Whether the useCombinedNoOverlap field is set.
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getUseCombinedNoOverlap
public boolean getUseCombinedNoOverlap()This can be beneficial if there is a lot of no-overlap constraints but a relatively low number of different intervals in the problem. Like 1000 intervals, but 1M intervals in the no-overlap constraints covering them.
optional bool use_combined_no_overlap = 133 [default = false];- Specified by:
getUseCombinedNoOverlapin interfaceSatParametersOrBuilder- Returns:
- The useCombinedNoOverlap.
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setUseCombinedNoOverlap
This can be beneficial if there is a lot of no-overlap constraints but a relatively low number of different intervals in the problem. Like 1000 intervals, but 1M intervals in the no-overlap constraints covering them.
optional bool use_combined_no_overlap = 133 [default = false];- Parameters:
value- The useCombinedNoOverlap to set.- Returns:
- This builder for chaining.
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clearUseCombinedNoOverlap
This can be beneficial if there is a lot of no-overlap constraints but a relatively low number of different intervals in the problem. Like 1000 intervals, but 1M intervals in the no-overlap constraints covering them.
optional bool use_combined_no_overlap = 133 [default = false];- Returns:
- This builder for chaining.
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hasAtMostOneMaxExpansionSize
public boolean hasAtMostOneMaxExpansionSize()All at_most_one constraints with a size <= param will be replaced by a quadratic number of binary implications.
optional int32 at_most_one_max_expansion_size = 270 [default = 3];- Specified by:
hasAtMostOneMaxExpansionSizein interfaceSatParametersOrBuilder- Returns:
- Whether the atMostOneMaxExpansionSize field is set.
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getAtMostOneMaxExpansionSize
public int getAtMostOneMaxExpansionSize()All at_most_one constraints with a size <= param will be replaced by a quadratic number of binary implications.
optional int32 at_most_one_max_expansion_size = 270 [default = 3];- Specified by:
getAtMostOneMaxExpansionSizein interfaceSatParametersOrBuilder- Returns:
- The atMostOneMaxExpansionSize.
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setAtMostOneMaxExpansionSize
All at_most_one constraints with a size <= param will be replaced by a quadratic number of binary implications.
optional int32 at_most_one_max_expansion_size = 270 [default = 3];- Parameters:
value- The atMostOneMaxExpansionSize to set.- Returns:
- This builder for chaining.
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clearAtMostOneMaxExpansionSize
All at_most_one constraints with a size <= param will be replaced by a quadratic number of binary implications.
optional int32 at_most_one_max_expansion_size = 270 [default = 3];- Returns:
- This builder for chaining.
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hasCatchSigintSignal
public boolean hasCatchSigintSignal()Indicates if the CP-SAT layer should catch Control-C (SIGINT) signals when calling solve. If set, catching the SIGINT signal will terminate the search gracefully, as if a time limit was reached.
optional bool catch_sigint_signal = 135 [default = true];- Specified by:
hasCatchSigintSignalin interfaceSatParametersOrBuilder- Returns:
- Whether the catchSigintSignal field is set.
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getCatchSigintSignal
public boolean getCatchSigintSignal()Indicates if the CP-SAT layer should catch Control-C (SIGINT) signals when calling solve. If set, catching the SIGINT signal will terminate the search gracefully, as if a time limit was reached.
optional bool catch_sigint_signal = 135 [default = true];- Specified by:
getCatchSigintSignalin interfaceSatParametersOrBuilder- Returns:
- The catchSigintSignal.
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setCatchSigintSignal
Indicates if the CP-SAT layer should catch Control-C (SIGINT) signals when calling solve. If set, catching the SIGINT signal will terminate the search gracefully, as if a time limit was reached.
optional bool catch_sigint_signal = 135 [default = true];- Parameters:
value- The catchSigintSignal to set.- Returns:
- This builder for chaining.
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clearCatchSigintSignal
Indicates if the CP-SAT layer should catch Control-C (SIGINT) signals when calling solve. If set, catching the SIGINT signal will terminate the search gracefully, as if a time limit was reached.
optional bool catch_sigint_signal = 135 [default = true];- Returns:
- This builder for chaining.
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hasUseImpliedBounds
public boolean hasUseImpliedBounds()Stores and exploits "implied-bounds" in the solver. That is, relations of the form literal => (var >= bound). This is currently used to derive stronger cuts.
optional bool use_implied_bounds = 144 [default = true];- Specified by:
hasUseImpliedBoundsin interfaceSatParametersOrBuilder- Returns:
- Whether the useImpliedBounds field is set.
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getUseImpliedBounds
public boolean getUseImpliedBounds()Stores and exploits "implied-bounds" in the solver. That is, relations of the form literal => (var >= bound). This is currently used to derive stronger cuts.
optional bool use_implied_bounds = 144 [default = true];- Specified by:
getUseImpliedBoundsin interfaceSatParametersOrBuilder- Returns:
- The useImpliedBounds.
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setUseImpliedBounds
Stores and exploits "implied-bounds" in the solver. That is, relations of the form literal => (var >= bound). This is currently used to derive stronger cuts.
optional bool use_implied_bounds = 144 [default = true];- Parameters:
value- The useImpliedBounds to set.- Returns:
- This builder for chaining.
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clearUseImpliedBounds
Stores and exploits "implied-bounds" in the solver. That is, relations of the form literal => (var >= bound). This is currently used to derive stronger cuts.
optional bool use_implied_bounds = 144 [default = true];- Returns:
- This builder for chaining.
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hasPolishLpSolution
public boolean hasPolishLpSolution()Whether we try to do a few degenerate iteration at the end of an LP solve to minimize the fractionality of the integer variable in the basis. This helps on some problems, but not so much on others. It also cost of bit of time to do such polish step.
optional bool polish_lp_solution = 175 [default = false];- Specified by:
hasPolishLpSolutionin interfaceSatParametersOrBuilder- Returns:
- Whether the polishLpSolution field is set.
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getPolishLpSolution
public boolean getPolishLpSolution()Whether we try to do a few degenerate iteration at the end of an LP solve to minimize the fractionality of the integer variable in the basis. This helps on some problems, but not so much on others. It also cost of bit of time to do such polish step.
optional bool polish_lp_solution = 175 [default = false];- Specified by:
getPolishLpSolutionin interfaceSatParametersOrBuilder- Returns:
- The polishLpSolution.
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setPolishLpSolution
Whether we try to do a few degenerate iteration at the end of an LP solve to minimize the fractionality of the integer variable in the basis. This helps on some problems, but not so much on others. It also cost of bit of time to do such polish step.
optional bool polish_lp_solution = 175 [default = false];- Parameters:
value- The polishLpSolution to set.- Returns:
- This builder for chaining.
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clearPolishLpSolution
Whether we try to do a few degenerate iteration at the end of an LP solve to minimize the fractionality of the integer variable in the basis. This helps on some problems, but not so much on others. It also cost of bit of time to do such polish step.
optional bool polish_lp_solution = 175 [default = false];- Returns:
- This builder for chaining.
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hasLpPrimalTolerance
public boolean hasLpPrimalTolerance()The internal LP tolerances used by CP-SAT. These applies to the internal and scaled problem. If the domains of your variables are large it might be good to use lower tolerances. If your problem is binary with low coefficients, it might be good to use higher ones to speed-up the lp solves.
optional double lp_primal_tolerance = 266 [default = 1e-07];- Specified by:
hasLpPrimalTolerancein interfaceSatParametersOrBuilder- Returns:
- Whether the lpPrimalTolerance field is set.
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getLpPrimalTolerance
public double getLpPrimalTolerance()The internal LP tolerances used by CP-SAT. These applies to the internal and scaled problem. If the domains of your variables are large it might be good to use lower tolerances. If your problem is binary with low coefficients, it might be good to use higher ones to speed-up the lp solves.
optional double lp_primal_tolerance = 266 [default = 1e-07];- Specified by:
getLpPrimalTolerancein interfaceSatParametersOrBuilder- Returns:
- The lpPrimalTolerance.
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setLpPrimalTolerance
The internal LP tolerances used by CP-SAT. These applies to the internal and scaled problem. If the domains of your variables are large it might be good to use lower tolerances. If your problem is binary with low coefficients, it might be good to use higher ones to speed-up the lp solves.
optional double lp_primal_tolerance = 266 [default = 1e-07];- Parameters:
value- The lpPrimalTolerance to set.- Returns:
- This builder for chaining.
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clearLpPrimalTolerance
The internal LP tolerances used by CP-SAT. These applies to the internal and scaled problem. If the domains of your variables are large it might be good to use lower tolerances. If your problem is binary with low coefficients, it might be good to use higher ones to speed-up the lp solves.
optional double lp_primal_tolerance = 266 [default = 1e-07];- Returns:
- This builder for chaining.
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hasLpDualTolerance
public boolean hasLpDualTolerance()optional double lp_dual_tolerance = 267 [default = 1e-07];- Specified by:
hasLpDualTolerancein interfaceSatParametersOrBuilder- Returns:
- Whether the lpDualTolerance field is set.
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getLpDualTolerance
public double getLpDualTolerance()optional double lp_dual_tolerance = 267 [default = 1e-07];- Specified by:
getLpDualTolerancein interfaceSatParametersOrBuilder- Returns:
- The lpDualTolerance.
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setLpDualTolerance
optional double lp_dual_tolerance = 267 [default = 1e-07];- Parameters:
value- The lpDualTolerance to set.- Returns:
- This builder for chaining.
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clearLpDualTolerance
optional double lp_dual_tolerance = 267 [default = 1e-07];- Returns:
- This builder for chaining.
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hasConvertIntervals
public boolean hasConvertIntervals()Temporary flag util the feature is more mature. This convert intervals to the newer proto format that support affine start/var/end instead of just variables.
optional bool convert_intervals = 177 [default = true];- Specified by:
hasConvertIntervalsin interfaceSatParametersOrBuilder- Returns:
- Whether the convertIntervals field is set.
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getConvertIntervals
public boolean getConvertIntervals()Temporary flag util the feature is more mature. This convert intervals to the newer proto format that support affine start/var/end instead of just variables.
optional bool convert_intervals = 177 [default = true];- Specified by:
getConvertIntervalsin interfaceSatParametersOrBuilder- Returns:
- The convertIntervals.
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setConvertIntervals
Temporary flag util the feature is more mature. This convert intervals to the newer proto format that support affine start/var/end instead of just variables.
optional bool convert_intervals = 177 [default = true];- Parameters:
value- The convertIntervals to set.- Returns:
- This builder for chaining.
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clearConvertIntervals
Temporary flag util the feature is more mature. This convert intervals to the newer proto format that support affine start/var/end instead of just variables.
optional bool convert_intervals = 177 [default = true];- Returns:
- This builder for chaining.
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hasSymmetryLevel
public boolean hasSymmetryLevel()Whether we try to automatically detect the symmetries in a model and exploit them. Currently, at level 1 we detect them in presolve and try to fix Booleans. At level 2, we also do some form of dynamic symmetry breaking during search. At level 3, we also detect symmetries for very large models, which can be slow. At level 4, we try to break as much symmetry as possible in presolve.
optional int32 symmetry_level = 183 [default = 2];- Specified by:
hasSymmetryLevelin interfaceSatParametersOrBuilder- Returns:
- Whether the symmetryLevel field is set.
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getSymmetryLevel
public int getSymmetryLevel()Whether we try to automatically detect the symmetries in a model and exploit them. Currently, at level 1 we detect them in presolve and try to fix Booleans. At level 2, we also do some form of dynamic symmetry breaking during search. At level 3, we also detect symmetries for very large models, which can be slow. At level 4, we try to break as much symmetry as possible in presolve.
optional int32 symmetry_level = 183 [default = 2];- Specified by:
getSymmetryLevelin interfaceSatParametersOrBuilder- Returns:
- The symmetryLevel.
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setSymmetryLevel
Whether we try to automatically detect the symmetries in a model and exploit them. Currently, at level 1 we detect them in presolve and try to fix Booleans. At level 2, we also do some form of dynamic symmetry breaking during search. At level 3, we also detect symmetries for very large models, which can be slow. At level 4, we try to break as much symmetry as possible in presolve.
optional int32 symmetry_level = 183 [default = 2];- Parameters:
value- The symmetryLevel to set.- Returns:
- This builder for chaining.
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clearSymmetryLevel
Whether we try to automatically detect the symmetries in a model and exploit them. Currently, at level 1 we detect them in presolve and try to fix Booleans. At level 2, we also do some form of dynamic symmetry breaking during search. At level 3, we also detect symmetries for very large models, which can be slow. At level 4, we try to break as much symmetry as possible in presolve.
optional int32 symmetry_level = 183 [default = 2];- Returns:
- This builder for chaining.
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hasUseSymmetryInLp
public boolean hasUseSymmetryInLp()When we have symmetry, it is possible to "fold" all variables from the same orbit into a single variable, while having the same power of LP relaxation. This can help significantly on symmetric problem. However there is currently a bit of overhead as the rest of the solver need to do some translation between the folded LP and the rest of the problem.
optional bool use_symmetry_in_lp = 301 [default = false];- Specified by:
hasUseSymmetryInLpin interfaceSatParametersOrBuilder- Returns:
- Whether the useSymmetryInLp field is set.
-
getUseSymmetryInLp
public boolean getUseSymmetryInLp()When we have symmetry, it is possible to "fold" all variables from the same orbit into a single variable, while having the same power of LP relaxation. This can help significantly on symmetric problem. However there is currently a bit of overhead as the rest of the solver need to do some translation between the folded LP and the rest of the problem.
optional bool use_symmetry_in_lp = 301 [default = false];- Specified by:
getUseSymmetryInLpin interfaceSatParametersOrBuilder- Returns:
- The useSymmetryInLp.
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setUseSymmetryInLp
When we have symmetry, it is possible to "fold" all variables from the same orbit into a single variable, while having the same power of LP relaxation. This can help significantly on symmetric problem. However there is currently a bit of overhead as the rest of the solver need to do some translation between the folded LP and the rest of the problem.
optional bool use_symmetry_in_lp = 301 [default = false];- Parameters:
value- The useSymmetryInLp to set.- Returns:
- This builder for chaining.
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clearUseSymmetryInLp
When we have symmetry, it is possible to "fold" all variables from the same orbit into a single variable, while having the same power of LP relaxation. This can help significantly on symmetric problem. However there is currently a bit of overhead as the rest of the solver need to do some translation between the folded LP and the rest of the problem.
optional bool use_symmetry_in_lp = 301 [default = false];- Returns:
- This builder for chaining.
-
hasKeepSymmetryInPresolve
public boolean hasKeepSymmetryInPresolve()Experimental. This will compute the symmetry of the problem once and for all. All presolve operations we do should keep the symmetry group intact or modify it properly. For now we have really little support for this. We will disable a bunch of presolve operations that could be supported.
optional bool keep_symmetry_in_presolve = 303 [default = false];- Specified by:
hasKeepSymmetryInPresolvein interfaceSatParametersOrBuilder- Returns:
- Whether the keepSymmetryInPresolve field is set.
-
getKeepSymmetryInPresolve
public boolean getKeepSymmetryInPresolve()Experimental. This will compute the symmetry of the problem once and for all. All presolve operations we do should keep the symmetry group intact or modify it properly. For now we have really little support for this. We will disable a bunch of presolve operations that could be supported.
optional bool keep_symmetry_in_presolve = 303 [default = false];- Specified by:
getKeepSymmetryInPresolvein interfaceSatParametersOrBuilder- Returns:
- The keepSymmetryInPresolve.
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setKeepSymmetryInPresolve
Experimental. This will compute the symmetry of the problem once and for all. All presolve operations we do should keep the symmetry group intact or modify it properly. For now we have really little support for this. We will disable a bunch of presolve operations that could be supported.
optional bool keep_symmetry_in_presolve = 303 [default = false];- Parameters:
value- The keepSymmetryInPresolve to set.- Returns:
- This builder for chaining.
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clearKeepSymmetryInPresolve
Experimental. This will compute the symmetry of the problem once and for all. All presolve operations we do should keep the symmetry group intact or modify it properly. For now we have really little support for this. We will disable a bunch of presolve operations that could be supported.
optional bool keep_symmetry_in_presolve = 303 [default = false];- Returns:
- This builder for chaining.
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hasSymmetryDetectionDeterministicTimeLimit
public boolean hasSymmetryDetectionDeterministicTimeLimit()Deterministic time limit for symmetry detection.
optional double symmetry_detection_deterministic_time_limit = 302 [default = 1];- Specified by:
hasSymmetryDetectionDeterministicTimeLimitin interfaceSatParametersOrBuilder- Returns:
- Whether the symmetryDetectionDeterministicTimeLimit field is set.
-
getSymmetryDetectionDeterministicTimeLimit
public double getSymmetryDetectionDeterministicTimeLimit()Deterministic time limit for symmetry detection.
optional double symmetry_detection_deterministic_time_limit = 302 [default = 1];- Specified by:
getSymmetryDetectionDeterministicTimeLimitin interfaceSatParametersOrBuilder- Returns:
- The symmetryDetectionDeterministicTimeLimit.
-
setSymmetryDetectionDeterministicTimeLimit
Deterministic time limit for symmetry detection.
optional double symmetry_detection_deterministic_time_limit = 302 [default = 1];- Parameters:
value- The symmetryDetectionDeterministicTimeLimit to set.- Returns:
- This builder for chaining.
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clearSymmetryDetectionDeterministicTimeLimit
Deterministic time limit for symmetry detection.
optional double symmetry_detection_deterministic_time_limit = 302 [default = 1];- Returns:
- This builder for chaining.
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hasNewLinearPropagation
public boolean hasNewLinearPropagation()The new linear propagation code treat all constraints at once and use an adaptation of Bellman-Ford-Tarjan to propagate constraint in a smarter order and potentially detect propagation cycle earlier.
optional bool new_linear_propagation = 224 [default = true];- Specified by:
hasNewLinearPropagationin interfaceSatParametersOrBuilder- Returns:
- Whether the newLinearPropagation field is set.
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getNewLinearPropagation
public boolean getNewLinearPropagation()The new linear propagation code treat all constraints at once and use an adaptation of Bellman-Ford-Tarjan to propagate constraint in a smarter order and potentially detect propagation cycle earlier.
optional bool new_linear_propagation = 224 [default = true];- Specified by:
getNewLinearPropagationin interfaceSatParametersOrBuilder- Returns:
- The newLinearPropagation.
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setNewLinearPropagation
The new linear propagation code treat all constraints at once and use an adaptation of Bellman-Ford-Tarjan to propagate constraint in a smarter order and potentially detect propagation cycle earlier.
optional bool new_linear_propagation = 224 [default = true];- Parameters:
value- The newLinearPropagation to set.- Returns:
- This builder for chaining.
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clearNewLinearPropagation
The new linear propagation code treat all constraints at once and use an adaptation of Bellman-Ford-Tarjan to propagate constraint in a smarter order and potentially detect propagation cycle earlier.
optional bool new_linear_propagation = 224 [default = true];- Returns:
- This builder for chaining.
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hasLinearSplitSize
public boolean hasLinearSplitSize()Linear constraints that are not pseudo-Boolean and that are longer than this size will be split into sqrt(size) intermediate sums in order to have faster propation in the CP engine.
optional int32 linear_split_size = 256 [default = 100];- Specified by:
hasLinearSplitSizein interfaceSatParametersOrBuilder- Returns:
- Whether the linearSplitSize field is set.
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getLinearSplitSize
public int getLinearSplitSize()Linear constraints that are not pseudo-Boolean and that are longer than this size will be split into sqrt(size) intermediate sums in order to have faster propation in the CP engine.
optional int32 linear_split_size = 256 [default = 100];- Specified by:
getLinearSplitSizein interfaceSatParametersOrBuilder- Returns:
- The linearSplitSize.
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setLinearSplitSize
Linear constraints that are not pseudo-Boolean and that are longer than this size will be split into sqrt(size) intermediate sums in order to have faster propation in the CP engine.
optional int32 linear_split_size = 256 [default = 100];- Parameters:
value- The linearSplitSize to set.- Returns:
- This builder for chaining.
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clearLinearSplitSize
Linear constraints that are not pseudo-Boolean and that are longer than this size will be split into sqrt(size) intermediate sums in order to have faster propation in the CP engine.
optional int32 linear_split_size = 256 [default = 100];- Returns:
- This builder for chaining.
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hasLinearizationLevel
public boolean hasLinearizationLevel()A non-negative level indicating the type of constraints we consider in the LP relaxation. At level zero, no LP relaxation is used. At level 1, only the linear constraint and full encoding are added. At level 2, we also add all the Boolean constraints.
optional int32 linearization_level = 90 [default = 1];- Specified by:
hasLinearizationLevelin interfaceSatParametersOrBuilder- Returns:
- Whether the linearizationLevel field is set.
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getLinearizationLevel
public int getLinearizationLevel()A non-negative level indicating the type of constraints we consider in the LP relaxation. At level zero, no LP relaxation is used. At level 1, only the linear constraint and full encoding are added. At level 2, we also add all the Boolean constraints.
optional int32 linearization_level = 90 [default = 1];- Specified by:
getLinearizationLevelin interfaceSatParametersOrBuilder- Returns:
- The linearizationLevel.
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setLinearizationLevel
A non-negative level indicating the type of constraints we consider in the LP relaxation. At level zero, no LP relaxation is used. At level 1, only the linear constraint and full encoding are added. At level 2, we also add all the Boolean constraints.
optional int32 linearization_level = 90 [default = 1];- Parameters:
value- The linearizationLevel to set.- Returns:
- This builder for chaining.
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clearLinearizationLevel
A non-negative level indicating the type of constraints we consider in the LP relaxation. At level zero, no LP relaxation is used. At level 1, only the linear constraint and full encoding are added. At level 2, we also add all the Boolean constraints.
optional int32 linearization_level = 90 [default = 1];- Returns:
- This builder for chaining.
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hasBooleanEncodingLevel
public boolean hasBooleanEncodingLevel()A non-negative level indicating how much we should try to fully encode Integer variables as Boolean.
optional int32 boolean_encoding_level = 107 [default = 1];- Specified by:
hasBooleanEncodingLevelin interfaceSatParametersOrBuilder- Returns:
- Whether the booleanEncodingLevel field is set.
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getBooleanEncodingLevel
public int getBooleanEncodingLevel()A non-negative level indicating how much we should try to fully encode Integer variables as Boolean.
optional int32 boolean_encoding_level = 107 [default = 1];- Specified by:
getBooleanEncodingLevelin interfaceSatParametersOrBuilder- Returns:
- The booleanEncodingLevel.
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setBooleanEncodingLevel
A non-negative level indicating how much we should try to fully encode Integer variables as Boolean.
optional int32 boolean_encoding_level = 107 [default = 1];- Parameters:
value- The booleanEncodingLevel to set.- Returns:
- This builder for chaining.
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clearBooleanEncodingLevel
A non-negative level indicating how much we should try to fully encode Integer variables as Boolean.
optional int32 boolean_encoding_level = 107 [default = 1];- Returns:
- This builder for chaining.
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hasMaxDomainSizeWhenEncodingEqNeqConstraints
public boolean hasMaxDomainSizeWhenEncodingEqNeqConstraints()When loading a*x + b*y ==/!= c when x and y are both fully encoded. The solver may decide to replace the linear equation by a set of clauses. This is triggered if the sizes of the domains of x and y are below the threshold.
optional int32 max_domain_size_when_encoding_eq_neq_constraints = 191 [default = 16];- Specified by:
hasMaxDomainSizeWhenEncodingEqNeqConstraintsin interfaceSatParametersOrBuilder- Returns:
- Whether the maxDomainSizeWhenEncodingEqNeqConstraints field is set.
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getMaxDomainSizeWhenEncodingEqNeqConstraints
public int getMaxDomainSizeWhenEncodingEqNeqConstraints()When loading a*x + b*y ==/!= c when x and y are both fully encoded. The solver may decide to replace the linear equation by a set of clauses. This is triggered if the sizes of the domains of x and y are below the threshold.
optional int32 max_domain_size_when_encoding_eq_neq_constraints = 191 [default = 16];- Specified by:
getMaxDomainSizeWhenEncodingEqNeqConstraintsin interfaceSatParametersOrBuilder- Returns:
- The maxDomainSizeWhenEncodingEqNeqConstraints.
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setMaxDomainSizeWhenEncodingEqNeqConstraints
When loading a*x + b*y ==/!= c when x and y are both fully encoded. The solver may decide to replace the linear equation by a set of clauses. This is triggered if the sizes of the domains of x and y are below the threshold.
optional int32 max_domain_size_when_encoding_eq_neq_constraints = 191 [default = 16];- Parameters:
value- The maxDomainSizeWhenEncodingEqNeqConstraints to set.- Returns:
- This builder for chaining.
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clearMaxDomainSizeWhenEncodingEqNeqConstraints
When loading a*x + b*y ==/!= c when x and y are both fully encoded. The solver may decide to replace the linear equation by a set of clauses. This is triggered if the sizes of the domains of x and y are below the threshold.
optional int32 max_domain_size_when_encoding_eq_neq_constraints = 191 [default = 16];- Returns:
- This builder for chaining.
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hasMaxNumCuts
public boolean hasMaxNumCuts()The limit on the number of cuts in our cut pool. When this is reached we do not generate cuts anymore. TODO(user): We should probably remove this parameters, and just always generate cuts but only keep the best n or something.
optional int32 max_num_cuts = 91 [default = 10000];- Specified by:
hasMaxNumCutsin interfaceSatParametersOrBuilder- Returns:
- Whether the maxNumCuts field is set.
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getMaxNumCuts
public int getMaxNumCuts()The limit on the number of cuts in our cut pool. When this is reached we do not generate cuts anymore. TODO(user): We should probably remove this parameters, and just always generate cuts but only keep the best n or something.
optional int32 max_num_cuts = 91 [default = 10000];- Specified by:
getMaxNumCutsin interfaceSatParametersOrBuilder- Returns:
- The maxNumCuts.
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setMaxNumCuts
The limit on the number of cuts in our cut pool. When this is reached we do not generate cuts anymore. TODO(user): We should probably remove this parameters, and just always generate cuts but only keep the best n or something.
optional int32 max_num_cuts = 91 [default = 10000];- Parameters:
value- The maxNumCuts to set.- Returns:
- This builder for chaining.
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clearMaxNumCuts
The limit on the number of cuts in our cut pool. When this is reached we do not generate cuts anymore. TODO(user): We should probably remove this parameters, and just always generate cuts but only keep the best n or something.
optional int32 max_num_cuts = 91 [default = 10000];- Returns:
- This builder for chaining.
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hasCutLevel
public boolean hasCutLevel()Control the global cut effort. Zero will turn off all cut. For now we just have one level. Note also that most cuts are only used at linearization level >= 2.
optional int32 cut_level = 196 [default = 1];- Specified by:
hasCutLevelin interfaceSatParametersOrBuilder- Returns:
- Whether the cutLevel field is set.
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getCutLevel
public int getCutLevel()Control the global cut effort. Zero will turn off all cut. For now we just have one level. Note also that most cuts are only used at linearization level >= 2.
optional int32 cut_level = 196 [default = 1];- Specified by:
getCutLevelin interfaceSatParametersOrBuilder- Returns:
- The cutLevel.
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setCutLevel
Control the global cut effort. Zero will turn off all cut. For now we just have one level. Note also that most cuts are only used at linearization level >= 2.
optional int32 cut_level = 196 [default = 1];- Parameters:
value- The cutLevel to set.- Returns:
- This builder for chaining.
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clearCutLevel
Control the global cut effort. Zero will turn off all cut. For now we just have one level. Note also that most cuts are only used at linearization level >= 2.
optional int32 cut_level = 196 [default = 1];- Returns:
- This builder for chaining.
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hasOnlyAddCutsAtLevelZero
public boolean hasOnlyAddCutsAtLevelZero()For the cut that can be generated at any level, this control if we only try to generate them at the root node.
optional bool only_add_cuts_at_level_zero = 92 [default = false];- Specified by:
hasOnlyAddCutsAtLevelZeroin interfaceSatParametersOrBuilder- Returns:
- Whether the onlyAddCutsAtLevelZero field is set.
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getOnlyAddCutsAtLevelZero
public boolean getOnlyAddCutsAtLevelZero()For the cut that can be generated at any level, this control if we only try to generate them at the root node.
optional bool only_add_cuts_at_level_zero = 92 [default = false];- Specified by:
getOnlyAddCutsAtLevelZeroin interfaceSatParametersOrBuilder- Returns:
- The onlyAddCutsAtLevelZero.
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setOnlyAddCutsAtLevelZero
For the cut that can be generated at any level, this control if we only try to generate them at the root node.
optional bool only_add_cuts_at_level_zero = 92 [default = false];- Parameters:
value- The onlyAddCutsAtLevelZero to set.- Returns:
- This builder for chaining.
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clearOnlyAddCutsAtLevelZero
For the cut that can be generated at any level, this control if we only try to generate them at the root node.
optional bool only_add_cuts_at_level_zero = 92 [default = false];- Returns:
- This builder for chaining.
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hasAddObjectiveCut
public boolean hasAddObjectiveCut()When the LP objective is fractional, do we add the cut that forces the linear objective expression to be greater or equal to this fractional value rounded up? We can always do that since our objective is integer, and combined with MIR heuristic to reduce the coefficient of such cut, it can help.
optional bool add_objective_cut = 197 [default = false];- Specified by:
hasAddObjectiveCutin interfaceSatParametersOrBuilder- Returns:
- Whether the addObjectiveCut field is set.
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getAddObjectiveCut
public boolean getAddObjectiveCut()When the LP objective is fractional, do we add the cut that forces the linear objective expression to be greater or equal to this fractional value rounded up? We can always do that since our objective is integer, and combined with MIR heuristic to reduce the coefficient of such cut, it can help.
optional bool add_objective_cut = 197 [default = false];- Specified by:
getAddObjectiveCutin interfaceSatParametersOrBuilder- Returns:
- The addObjectiveCut.
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setAddObjectiveCut
When the LP objective is fractional, do we add the cut that forces the linear objective expression to be greater or equal to this fractional value rounded up? We can always do that since our objective is integer, and combined with MIR heuristic to reduce the coefficient of such cut, it can help.
optional bool add_objective_cut = 197 [default = false];- Parameters:
value- The addObjectiveCut to set.- Returns:
- This builder for chaining.
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clearAddObjectiveCut
When the LP objective is fractional, do we add the cut that forces the linear objective expression to be greater or equal to this fractional value rounded up? We can always do that since our objective is integer, and combined with MIR heuristic to reduce the coefficient of such cut, it can help.
optional bool add_objective_cut = 197 [default = false];- Returns:
- This builder for chaining.
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hasAddCgCuts
public boolean hasAddCgCuts()Whether we generate and add Chvatal-Gomory cuts to the LP at root node. Note that for now, this is not heavily tuned.
optional bool add_cg_cuts = 117 [default = true];- Specified by:
hasAddCgCutsin interfaceSatParametersOrBuilder- Returns:
- Whether the addCgCuts field is set.
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getAddCgCuts
public boolean getAddCgCuts()Whether we generate and add Chvatal-Gomory cuts to the LP at root node. Note that for now, this is not heavily tuned.
optional bool add_cg_cuts = 117 [default = true];- Specified by:
getAddCgCutsin interfaceSatParametersOrBuilder- Returns:
- The addCgCuts.
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setAddCgCuts
Whether we generate and add Chvatal-Gomory cuts to the LP at root node. Note that for now, this is not heavily tuned.
optional bool add_cg_cuts = 117 [default = true];- Parameters:
value- The addCgCuts to set.- Returns:
- This builder for chaining.
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clearAddCgCuts
Whether we generate and add Chvatal-Gomory cuts to the LP at root node. Note that for now, this is not heavily tuned.
optional bool add_cg_cuts = 117 [default = true];- Returns:
- This builder for chaining.
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hasAddMirCuts
public boolean hasAddMirCuts()Whether we generate MIR cuts at root node. Note that for now, this is not heavily tuned.
optional bool add_mir_cuts = 120 [default = true];- Specified by:
hasAddMirCutsin interfaceSatParametersOrBuilder- Returns:
- Whether the addMirCuts field is set.
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getAddMirCuts
public boolean getAddMirCuts()Whether we generate MIR cuts at root node. Note that for now, this is not heavily tuned.
optional bool add_mir_cuts = 120 [default = true];- Specified by:
getAddMirCutsin interfaceSatParametersOrBuilder- Returns:
- The addMirCuts.
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setAddMirCuts
Whether we generate MIR cuts at root node. Note that for now, this is not heavily tuned.
optional bool add_mir_cuts = 120 [default = true];- Parameters:
value- The addMirCuts to set.- Returns:
- This builder for chaining.
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clearAddMirCuts
Whether we generate MIR cuts at root node. Note that for now, this is not heavily tuned.
optional bool add_mir_cuts = 120 [default = true];- Returns:
- This builder for chaining.
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hasAddZeroHalfCuts
public boolean hasAddZeroHalfCuts()Whether we generate Zero-Half cuts at root node. Note that for now, this is not heavily tuned.
optional bool add_zero_half_cuts = 169 [default = true];- Specified by:
hasAddZeroHalfCutsin interfaceSatParametersOrBuilder- Returns:
- Whether the addZeroHalfCuts field is set.
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getAddZeroHalfCuts
public boolean getAddZeroHalfCuts()Whether we generate Zero-Half cuts at root node. Note that for now, this is not heavily tuned.
optional bool add_zero_half_cuts = 169 [default = true];- Specified by:
getAddZeroHalfCutsin interfaceSatParametersOrBuilder- Returns:
- The addZeroHalfCuts.
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setAddZeroHalfCuts
Whether we generate Zero-Half cuts at root node. Note that for now, this is not heavily tuned.
optional bool add_zero_half_cuts = 169 [default = true];- Parameters:
value- The addZeroHalfCuts to set.- Returns:
- This builder for chaining.
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clearAddZeroHalfCuts
Whether we generate Zero-Half cuts at root node. Note that for now, this is not heavily tuned.
optional bool add_zero_half_cuts = 169 [default = true];- Returns:
- This builder for chaining.
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hasAddCliqueCuts
public boolean hasAddCliqueCuts()Whether we generate clique cuts from the binary implication graph. Note that as the search goes on, this graph will contains new binary clauses learned by the SAT engine.
optional bool add_clique_cuts = 172 [default = true];- Specified by:
hasAddCliqueCutsin interfaceSatParametersOrBuilder- Returns:
- Whether the addCliqueCuts field is set.
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getAddCliqueCuts
public boolean getAddCliqueCuts()Whether we generate clique cuts from the binary implication graph. Note that as the search goes on, this graph will contains new binary clauses learned by the SAT engine.
optional bool add_clique_cuts = 172 [default = true];- Specified by:
getAddCliqueCutsin interfaceSatParametersOrBuilder- Returns:
- The addCliqueCuts.
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setAddCliqueCuts
Whether we generate clique cuts from the binary implication graph. Note that as the search goes on, this graph will contains new binary clauses learned by the SAT engine.
optional bool add_clique_cuts = 172 [default = true];- Parameters:
value- The addCliqueCuts to set.- Returns:
- This builder for chaining.
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clearAddCliqueCuts
Whether we generate clique cuts from the binary implication graph. Note that as the search goes on, this graph will contains new binary clauses learned by the SAT engine.
optional bool add_clique_cuts = 172 [default = true];- Returns:
- This builder for chaining.
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hasAddRltCuts
public boolean hasAddRltCuts()Whether we generate RLT cuts. This is still experimental but can help on binary problem with a lot of clauses of size 3.
optional bool add_rlt_cuts = 279 [default = true];- Specified by:
hasAddRltCutsin interfaceSatParametersOrBuilder- Returns:
- Whether the addRltCuts field is set.
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getAddRltCuts
public boolean getAddRltCuts()Whether we generate RLT cuts. This is still experimental but can help on binary problem with a lot of clauses of size 3.
optional bool add_rlt_cuts = 279 [default = true];- Specified by:
getAddRltCutsin interfaceSatParametersOrBuilder- Returns:
- The addRltCuts.
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setAddRltCuts
Whether we generate RLT cuts. This is still experimental but can help on binary problem with a lot of clauses of size 3.
optional bool add_rlt_cuts = 279 [default = true];- Parameters:
value- The addRltCuts to set.- Returns:
- This builder for chaining.
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clearAddRltCuts
Whether we generate RLT cuts. This is still experimental but can help on binary problem with a lot of clauses of size 3.
optional bool add_rlt_cuts = 279 [default = true];- Returns:
- This builder for chaining.
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hasMaxAllDiffCutSize
public boolean hasMaxAllDiffCutSize()Cut generator for all diffs can add too many cuts for large all_diff constraints. This parameter restricts the large all_diff constraints to have a cut generator.
optional int32 max_all_diff_cut_size = 148 [default = 64];- Specified by:
hasMaxAllDiffCutSizein interfaceSatParametersOrBuilder- Returns:
- Whether the maxAllDiffCutSize field is set.
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getMaxAllDiffCutSize
public int getMaxAllDiffCutSize()Cut generator for all diffs can add too many cuts for large all_diff constraints. This parameter restricts the large all_diff constraints to have a cut generator.
optional int32 max_all_diff_cut_size = 148 [default = 64];- Specified by:
getMaxAllDiffCutSizein interfaceSatParametersOrBuilder- Returns:
- The maxAllDiffCutSize.
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setMaxAllDiffCutSize
Cut generator for all diffs can add too many cuts for large all_diff constraints. This parameter restricts the large all_diff constraints to have a cut generator.
optional int32 max_all_diff_cut_size = 148 [default = 64];- Parameters:
value- The maxAllDiffCutSize to set.- Returns:
- This builder for chaining.
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clearMaxAllDiffCutSize
Cut generator for all diffs can add too many cuts for large all_diff constraints. This parameter restricts the large all_diff constraints to have a cut generator.
optional int32 max_all_diff_cut_size = 148 [default = 64];- Returns:
- This builder for chaining.
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hasAddLinMaxCuts
public boolean hasAddLinMaxCuts()For the lin max constraints, generates the cuts described in "Strong mixed-integer programming formulations for trained neural networks" by Ross Anderson et. (https://arxiv.org/pdf/1811.01988.pdf)
optional bool add_lin_max_cuts = 152 [default = true];- Specified by:
hasAddLinMaxCutsin interfaceSatParametersOrBuilder- Returns:
- Whether the addLinMaxCuts field is set.
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getAddLinMaxCuts
public boolean getAddLinMaxCuts()For the lin max constraints, generates the cuts described in "Strong mixed-integer programming formulations for trained neural networks" by Ross Anderson et. (https://arxiv.org/pdf/1811.01988.pdf)
optional bool add_lin_max_cuts = 152 [default = true];- Specified by:
getAddLinMaxCutsin interfaceSatParametersOrBuilder- Returns:
- The addLinMaxCuts.
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setAddLinMaxCuts
For the lin max constraints, generates the cuts described in "Strong mixed-integer programming formulations for trained neural networks" by Ross Anderson et. (https://arxiv.org/pdf/1811.01988.pdf)
optional bool add_lin_max_cuts = 152 [default = true];- Parameters:
value- The addLinMaxCuts to set.- Returns:
- This builder for chaining.
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clearAddLinMaxCuts
For the lin max constraints, generates the cuts described in "Strong mixed-integer programming formulations for trained neural networks" by Ross Anderson et. (https://arxiv.org/pdf/1811.01988.pdf)
optional bool add_lin_max_cuts = 152 [default = true];- Returns:
- This builder for chaining.
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hasMaxIntegerRoundingScaling
public boolean hasMaxIntegerRoundingScaling()In the integer rounding procedure used for MIR and Gomory cut, the maximum "scaling" we use (must be positive). The lower this is, the lower the integer coefficients of the cut will be. Note that cut generated by lower values are not necessarily worse than cut generated by larger value. There is no strict dominance relationship. Setting this to 2 result in the "strong fractional rouding" of Letchford and Lodi.
optional int32 max_integer_rounding_scaling = 119 [default = 600];- Specified by:
hasMaxIntegerRoundingScalingin interfaceSatParametersOrBuilder- Returns:
- Whether the maxIntegerRoundingScaling field is set.
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getMaxIntegerRoundingScaling
public int getMaxIntegerRoundingScaling()In the integer rounding procedure used for MIR and Gomory cut, the maximum "scaling" we use (must be positive). The lower this is, the lower the integer coefficients of the cut will be. Note that cut generated by lower values are not necessarily worse than cut generated by larger value. There is no strict dominance relationship. Setting this to 2 result in the "strong fractional rouding" of Letchford and Lodi.
optional int32 max_integer_rounding_scaling = 119 [default = 600];- Specified by:
getMaxIntegerRoundingScalingin interfaceSatParametersOrBuilder- Returns:
- The maxIntegerRoundingScaling.
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setMaxIntegerRoundingScaling
In the integer rounding procedure used for MIR and Gomory cut, the maximum "scaling" we use (must be positive). The lower this is, the lower the integer coefficients of the cut will be. Note that cut generated by lower values are not necessarily worse than cut generated by larger value. There is no strict dominance relationship. Setting this to 2 result in the "strong fractional rouding" of Letchford and Lodi.
optional int32 max_integer_rounding_scaling = 119 [default = 600];- Parameters:
value- The maxIntegerRoundingScaling to set.- Returns:
- This builder for chaining.
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clearMaxIntegerRoundingScaling
In the integer rounding procedure used for MIR and Gomory cut, the maximum "scaling" we use (must be positive). The lower this is, the lower the integer coefficients of the cut will be. Note that cut generated by lower values are not necessarily worse than cut generated by larger value. There is no strict dominance relationship. Setting this to 2 result in the "strong fractional rouding" of Letchford and Lodi.
optional int32 max_integer_rounding_scaling = 119 [default = 600];- Returns:
- This builder for chaining.
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hasAddLpConstraintsLazily
public boolean hasAddLpConstraintsLazily()If true, we start by an empty LP, and only add constraints not satisfied by the current LP solution batch by batch. A constraint that is only added like this is known as a "lazy" constraint in the literature, except that we currently consider all constraints as lazy here.
optional bool add_lp_constraints_lazily = 112 [default = true];- Specified by:
hasAddLpConstraintsLazilyin interfaceSatParametersOrBuilder- Returns:
- Whether the addLpConstraintsLazily field is set.
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getAddLpConstraintsLazily
public boolean getAddLpConstraintsLazily()If true, we start by an empty LP, and only add constraints not satisfied by the current LP solution batch by batch. A constraint that is only added like this is known as a "lazy" constraint in the literature, except that we currently consider all constraints as lazy here.
optional bool add_lp_constraints_lazily = 112 [default = true];- Specified by:
getAddLpConstraintsLazilyin interfaceSatParametersOrBuilder- Returns:
- The addLpConstraintsLazily.
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setAddLpConstraintsLazily
If true, we start by an empty LP, and only add constraints not satisfied by the current LP solution batch by batch. A constraint that is only added like this is known as a "lazy" constraint in the literature, except that we currently consider all constraints as lazy here.
optional bool add_lp_constraints_lazily = 112 [default = true];- Parameters:
value- The addLpConstraintsLazily to set.- Returns:
- This builder for chaining.
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clearAddLpConstraintsLazily
If true, we start by an empty LP, and only add constraints not satisfied by the current LP solution batch by batch. A constraint that is only added like this is known as a "lazy" constraint in the literature, except that we currently consider all constraints as lazy here.
optional bool add_lp_constraints_lazily = 112 [default = true];- Returns:
- This builder for chaining.
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hasRootLpIterations
public boolean hasRootLpIterations()Even at the root node, we do not want to spend too much time on the LP if it is "difficult". So we solve it in "chunks" of that many iterations. The solve will be continued down in the tree or the next time we go back to the root node.
optional int32 root_lp_iterations = 227 [default = 2000];- Specified by:
hasRootLpIterationsin interfaceSatParametersOrBuilder- Returns:
- Whether the rootLpIterations field is set.
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getRootLpIterations
public int getRootLpIterations()Even at the root node, we do not want to spend too much time on the LP if it is "difficult". So we solve it in "chunks" of that many iterations. The solve will be continued down in the tree or the next time we go back to the root node.
optional int32 root_lp_iterations = 227 [default = 2000];- Specified by:
getRootLpIterationsin interfaceSatParametersOrBuilder- Returns:
- The rootLpIterations.
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setRootLpIterations
Even at the root node, we do not want to spend too much time on the LP if it is "difficult". So we solve it in "chunks" of that many iterations. The solve will be continued down in the tree or the next time we go back to the root node.
optional int32 root_lp_iterations = 227 [default = 2000];- Parameters:
value- The rootLpIterations to set.- Returns:
- This builder for chaining.
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clearRootLpIterations
Even at the root node, we do not want to spend too much time on the LP if it is "difficult". So we solve it in "chunks" of that many iterations. The solve will be continued down in the tree or the next time we go back to the root node.
optional int32 root_lp_iterations = 227 [default = 2000];- Returns:
- This builder for chaining.
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hasMinOrthogonalityForLpConstraints
public boolean hasMinOrthogonalityForLpConstraints()While adding constraints, skip the constraints which have orthogonality less than 'min_orthogonality_for_lp_constraints' with already added constraints during current call. Orthogonality is defined as 1 - cosine(vector angle between constraints). A value of zero disable this feature.
optional double min_orthogonality_for_lp_constraints = 115 [default = 0.05];- Specified by:
hasMinOrthogonalityForLpConstraintsin interfaceSatParametersOrBuilder- Returns:
- Whether the minOrthogonalityForLpConstraints field is set.
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getMinOrthogonalityForLpConstraints
public double getMinOrthogonalityForLpConstraints()While adding constraints, skip the constraints which have orthogonality less than 'min_orthogonality_for_lp_constraints' with already added constraints during current call. Orthogonality is defined as 1 - cosine(vector angle between constraints). A value of zero disable this feature.
optional double min_orthogonality_for_lp_constraints = 115 [default = 0.05];- Specified by:
getMinOrthogonalityForLpConstraintsin interfaceSatParametersOrBuilder- Returns:
- The minOrthogonalityForLpConstraints.
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setMinOrthogonalityForLpConstraints
While adding constraints, skip the constraints which have orthogonality less than 'min_orthogonality_for_lp_constraints' with already added constraints during current call. Orthogonality is defined as 1 - cosine(vector angle between constraints). A value of zero disable this feature.
optional double min_orthogonality_for_lp_constraints = 115 [default = 0.05];- Parameters:
value- The minOrthogonalityForLpConstraints to set.- Returns:
- This builder for chaining.
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clearMinOrthogonalityForLpConstraints
While adding constraints, skip the constraints which have orthogonality less than 'min_orthogonality_for_lp_constraints' with already added constraints during current call. Orthogonality is defined as 1 - cosine(vector angle between constraints). A value of zero disable this feature.
optional double min_orthogonality_for_lp_constraints = 115 [default = 0.05];- Returns:
- This builder for chaining.
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hasMaxCutRoundsAtLevelZero
public boolean hasMaxCutRoundsAtLevelZero()Max number of time we perform cut generation and resolve the LP at level 0.
optional int32 max_cut_rounds_at_level_zero = 154 [default = 1];- Specified by:
hasMaxCutRoundsAtLevelZeroin interfaceSatParametersOrBuilder- Returns:
- Whether the maxCutRoundsAtLevelZero field is set.
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getMaxCutRoundsAtLevelZero
public int getMaxCutRoundsAtLevelZero()Max number of time we perform cut generation and resolve the LP at level 0.
optional int32 max_cut_rounds_at_level_zero = 154 [default = 1];- Specified by:
getMaxCutRoundsAtLevelZeroin interfaceSatParametersOrBuilder- Returns:
- The maxCutRoundsAtLevelZero.
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setMaxCutRoundsAtLevelZero
Max number of time we perform cut generation and resolve the LP at level 0.
optional int32 max_cut_rounds_at_level_zero = 154 [default = 1];- Parameters:
value- The maxCutRoundsAtLevelZero to set.- Returns:
- This builder for chaining.
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clearMaxCutRoundsAtLevelZero
Max number of time we perform cut generation and resolve the LP at level 0.
optional int32 max_cut_rounds_at_level_zero = 154 [default = 1];- Returns:
- This builder for chaining.
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hasMaxConsecutiveInactiveCount
public boolean hasMaxConsecutiveInactiveCount()If a constraint/cut in LP is not active for that many consecutive OPTIMAL solves, remove it from the LP. Note that it might be added again later if it become violated by the current LP solution.
optional int32 max_consecutive_inactive_count = 121 [default = 100];- Specified by:
hasMaxConsecutiveInactiveCountin interfaceSatParametersOrBuilder- Returns:
- Whether the maxConsecutiveInactiveCount field is set.
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getMaxConsecutiveInactiveCount
public int getMaxConsecutiveInactiveCount()If a constraint/cut in LP is not active for that many consecutive OPTIMAL solves, remove it from the LP. Note that it might be added again later if it become violated by the current LP solution.
optional int32 max_consecutive_inactive_count = 121 [default = 100];- Specified by:
getMaxConsecutiveInactiveCountin interfaceSatParametersOrBuilder- Returns:
- The maxConsecutiveInactiveCount.
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setMaxConsecutiveInactiveCount
If a constraint/cut in LP is not active for that many consecutive OPTIMAL solves, remove it from the LP. Note that it might be added again later if it become violated by the current LP solution.
optional int32 max_consecutive_inactive_count = 121 [default = 100];- Parameters:
value- The maxConsecutiveInactiveCount to set.- Returns:
- This builder for chaining.
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clearMaxConsecutiveInactiveCount
If a constraint/cut in LP is not active for that many consecutive OPTIMAL solves, remove it from the LP. Note that it might be added again later if it become violated by the current LP solution.
optional int32 max_consecutive_inactive_count = 121 [default = 100];- Returns:
- This builder for chaining.
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hasCutMaxActiveCountValue
public boolean hasCutMaxActiveCountValue()These parameters are similar to sat clause management activity parameters. They are effective only if the number of generated cuts exceed the storage limit. Default values are based on a few experiments on miplib instances.
optional double cut_max_active_count_value = 155 [default = 10000000000];- Specified by:
hasCutMaxActiveCountValuein interfaceSatParametersOrBuilder- Returns:
- Whether the cutMaxActiveCountValue field is set.
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getCutMaxActiveCountValue
public double getCutMaxActiveCountValue()These parameters are similar to sat clause management activity parameters. They are effective only if the number of generated cuts exceed the storage limit. Default values are based on a few experiments on miplib instances.
optional double cut_max_active_count_value = 155 [default = 10000000000];- Specified by:
getCutMaxActiveCountValuein interfaceSatParametersOrBuilder- Returns:
- The cutMaxActiveCountValue.
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setCutMaxActiveCountValue
These parameters are similar to sat clause management activity parameters. They are effective only if the number of generated cuts exceed the storage limit. Default values are based on a few experiments on miplib instances.
optional double cut_max_active_count_value = 155 [default = 10000000000];- Parameters:
value- The cutMaxActiveCountValue to set.- Returns:
- This builder for chaining.
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clearCutMaxActiveCountValue
These parameters are similar to sat clause management activity parameters. They are effective only if the number of generated cuts exceed the storage limit. Default values are based on a few experiments on miplib instances.
optional double cut_max_active_count_value = 155 [default = 10000000000];- Returns:
- This builder for chaining.
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hasCutActiveCountDecay
public boolean hasCutActiveCountDecay()optional double cut_active_count_decay = 156 [default = 0.8];- Specified by:
hasCutActiveCountDecayin interfaceSatParametersOrBuilder- Returns:
- Whether the cutActiveCountDecay field is set.
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getCutActiveCountDecay
public double getCutActiveCountDecay()optional double cut_active_count_decay = 156 [default = 0.8];- Specified by:
getCutActiveCountDecayin interfaceSatParametersOrBuilder- Returns:
- The cutActiveCountDecay.
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setCutActiveCountDecay
optional double cut_active_count_decay = 156 [default = 0.8];- Parameters:
value- The cutActiveCountDecay to set.- Returns:
- This builder for chaining.
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clearCutActiveCountDecay
optional double cut_active_count_decay = 156 [default = 0.8];- Returns:
- This builder for chaining.
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hasCutCleanupTarget
public boolean hasCutCleanupTarget()Target number of constraints to remove during cleanup.
optional int32 cut_cleanup_target = 157 [default = 1000];- Specified by:
hasCutCleanupTargetin interfaceSatParametersOrBuilder- Returns:
- Whether the cutCleanupTarget field is set.
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getCutCleanupTarget
public int getCutCleanupTarget()Target number of constraints to remove during cleanup.
optional int32 cut_cleanup_target = 157 [default = 1000];- Specified by:
getCutCleanupTargetin interfaceSatParametersOrBuilder- Returns:
- The cutCleanupTarget.
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setCutCleanupTarget
Target number of constraints to remove during cleanup.
optional int32 cut_cleanup_target = 157 [default = 1000];- Parameters:
value- The cutCleanupTarget to set.- Returns:
- This builder for chaining.
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clearCutCleanupTarget
Target number of constraints to remove during cleanup.
optional int32 cut_cleanup_target = 157 [default = 1000];- Returns:
- This builder for chaining.
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hasNewConstraintsBatchSize
public boolean hasNewConstraintsBatchSize()Add that many lazy constraints (or cuts) at once in the LP. Note that at the beginning of the solve, we do add more than this.
optional int32 new_constraints_batch_size = 122 [default = 50];- Specified by:
hasNewConstraintsBatchSizein interfaceSatParametersOrBuilder- Returns:
- Whether the newConstraintsBatchSize field is set.
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getNewConstraintsBatchSize
public int getNewConstraintsBatchSize()Add that many lazy constraints (or cuts) at once in the LP. Note that at the beginning of the solve, we do add more than this.
optional int32 new_constraints_batch_size = 122 [default = 50];- Specified by:
getNewConstraintsBatchSizein interfaceSatParametersOrBuilder- Returns:
- The newConstraintsBatchSize.
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setNewConstraintsBatchSize
Add that many lazy constraints (or cuts) at once in the LP. Note that at the beginning of the solve, we do add more than this.
optional int32 new_constraints_batch_size = 122 [default = 50];- Parameters:
value- The newConstraintsBatchSize to set.- Returns:
- This builder for chaining.
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clearNewConstraintsBatchSize
Add that many lazy constraints (or cuts) at once in the LP. Note that at the beginning of the solve, we do add more than this.
optional int32 new_constraints_batch_size = 122 [default = 50];- Returns:
- This builder for chaining.
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hasExploitIntegerLpSolution
public boolean hasExploitIntegerLpSolution()If true and the Lp relaxation of the problem has an integer optimal solution, try to exploit it. Note that since the LP relaxation may not contain all the constraints, such a solution is not necessarily a solution of the full problem.
optional bool exploit_integer_lp_solution = 94 [default = true];- Specified by:
hasExploitIntegerLpSolutionin interfaceSatParametersOrBuilder- Returns:
- Whether the exploitIntegerLpSolution field is set.
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getExploitIntegerLpSolution
public boolean getExploitIntegerLpSolution()If true and the Lp relaxation of the problem has an integer optimal solution, try to exploit it. Note that since the LP relaxation may not contain all the constraints, such a solution is not necessarily a solution of the full problem.
optional bool exploit_integer_lp_solution = 94 [default = true];- Specified by:
getExploitIntegerLpSolutionin interfaceSatParametersOrBuilder- Returns:
- The exploitIntegerLpSolution.
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setExploitIntegerLpSolution
If true and the Lp relaxation of the problem has an integer optimal solution, try to exploit it. Note that since the LP relaxation may not contain all the constraints, such a solution is not necessarily a solution of the full problem.
optional bool exploit_integer_lp_solution = 94 [default = true];- Parameters:
value- The exploitIntegerLpSolution to set.- Returns:
- This builder for chaining.
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clearExploitIntegerLpSolution
If true and the Lp relaxation of the problem has an integer optimal solution, try to exploit it. Note that since the LP relaxation may not contain all the constraints, such a solution is not necessarily a solution of the full problem.
optional bool exploit_integer_lp_solution = 94 [default = true];- Returns:
- This builder for chaining.
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hasExploitAllLpSolution
public boolean hasExploitAllLpSolution()If true and the Lp relaxation of the problem has a solution, try to exploit it. This is same as above except in this case the lp solution might not be an integer solution.
optional bool exploit_all_lp_solution = 116 [default = true];- Specified by:
hasExploitAllLpSolutionin interfaceSatParametersOrBuilder- Returns:
- Whether the exploitAllLpSolution field is set.
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getExploitAllLpSolution
public boolean getExploitAllLpSolution()If true and the Lp relaxation of the problem has a solution, try to exploit it. This is same as above except in this case the lp solution might not be an integer solution.
optional bool exploit_all_lp_solution = 116 [default = true];- Specified by:
getExploitAllLpSolutionin interfaceSatParametersOrBuilder- Returns:
- The exploitAllLpSolution.
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setExploitAllLpSolution
If true and the Lp relaxation of the problem has a solution, try to exploit it. This is same as above except in this case the lp solution might not be an integer solution.
optional bool exploit_all_lp_solution = 116 [default = true];- Parameters:
value- The exploitAllLpSolution to set.- Returns:
- This builder for chaining.
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clearExploitAllLpSolution
If true and the Lp relaxation of the problem has a solution, try to exploit it. This is same as above except in this case the lp solution might not be an integer solution.
optional bool exploit_all_lp_solution = 116 [default = true];- Returns:
- This builder for chaining.
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hasExploitBestSolution
public boolean hasExploitBestSolution()When branching on a variable, follow the last best solution value.
optional bool exploit_best_solution = 130 [default = false];- Specified by:
hasExploitBestSolutionin interfaceSatParametersOrBuilder- Returns:
- Whether the exploitBestSolution field is set.
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getExploitBestSolution
public boolean getExploitBestSolution()When branching on a variable, follow the last best solution value.
optional bool exploit_best_solution = 130 [default = false];- Specified by:
getExploitBestSolutionin interfaceSatParametersOrBuilder- Returns:
- The exploitBestSolution.
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setExploitBestSolution
When branching on a variable, follow the last best solution value.
optional bool exploit_best_solution = 130 [default = false];- Parameters:
value- The exploitBestSolution to set.- Returns:
- This builder for chaining.
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clearExploitBestSolution
When branching on a variable, follow the last best solution value.
optional bool exploit_best_solution = 130 [default = false];- Returns:
- This builder for chaining.
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hasExploitRelaxationSolution
public boolean hasExploitRelaxationSolution()When branching on a variable, follow the last best relaxation solution value. We use the relaxation with the tightest bound on the objective as the best relaxation solution.
optional bool exploit_relaxation_solution = 161 [default = false];- Specified by:
hasExploitRelaxationSolutionin interfaceSatParametersOrBuilder- Returns:
- Whether the exploitRelaxationSolution field is set.
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getExploitRelaxationSolution
public boolean getExploitRelaxationSolution()When branching on a variable, follow the last best relaxation solution value. We use the relaxation with the tightest bound on the objective as the best relaxation solution.
optional bool exploit_relaxation_solution = 161 [default = false];- Specified by:
getExploitRelaxationSolutionin interfaceSatParametersOrBuilder- Returns:
- The exploitRelaxationSolution.
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setExploitRelaxationSolution
When branching on a variable, follow the last best relaxation solution value. We use the relaxation with the tightest bound on the objective as the best relaxation solution.
optional bool exploit_relaxation_solution = 161 [default = false];- Parameters:
value- The exploitRelaxationSolution to set.- Returns:
- This builder for chaining.
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clearExploitRelaxationSolution
When branching on a variable, follow the last best relaxation solution value. We use the relaxation with the tightest bound on the objective as the best relaxation solution.
optional bool exploit_relaxation_solution = 161 [default = false];- Returns:
- This builder for chaining.
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hasExploitObjective
public boolean hasExploitObjective()When branching an a variable that directly affect the objective, branch on the value that lead to the best objective first.
optional bool exploit_objective = 131 [default = true];- Specified by:
hasExploitObjectivein interfaceSatParametersOrBuilder- Returns:
- Whether the exploitObjective field is set.
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getExploitObjective
public boolean getExploitObjective()When branching an a variable that directly affect the objective, branch on the value that lead to the best objective first.
optional bool exploit_objective = 131 [default = true];- Specified by:
getExploitObjectivein interfaceSatParametersOrBuilder- Returns:
- The exploitObjective.
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setExploitObjective
When branching an a variable that directly affect the objective, branch on the value that lead to the best objective first.
optional bool exploit_objective = 131 [default = true];- Parameters:
value- The exploitObjective to set.- Returns:
- This builder for chaining.
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clearExploitObjective
When branching an a variable that directly affect the objective, branch on the value that lead to the best objective first.
optional bool exploit_objective = 131 [default = true];- Returns:
- This builder for chaining.
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hasDetectLinearizedProduct
public boolean hasDetectLinearizedProduct()Infer products of Boolean or of Boolean time IntegerVariable from the linear constrainst in the problem. This can be used in some cuts, altough for now we don't really exploit it.
optional bool detect_linearized_product = 277 [default = false];- Specified by:
hasDetectLinearizedProductin interfaceSatParametersOrBuilder- Returns:
- Whether the detectLinearizedProduct field is set.
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getDetectLinearizedProduct
public boolean getDetectLinearizedProduct()Infer products of Boolean or of Boolean time IntegerVariable from the linear constrainst in the problem. This can be used in some cuts, altough for now we don't really exploit it.
optional bool detect_linearized_product = 277 [default = false];- Specified by:
getDetectLinearizedProductin interfaceSatParametersOrBuilder- Returns:
- The detectLinearizedProduct.
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setDetectLinearizedProduct
Infer products of Boolean or of Boolean time IntegerVariable from the linear constrainst in the problem. This can be used in some cuts, altough for now we don't really exploit it.
optional bool detect_linearized_product = 277 [default = false];- Parameters:
value- The detectLinearizedProduct to set.- Returns:
- This builder for chaining.
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clearDetectLinearizedProduct
Infer products of Boolean or of Boolean time IntegerVariable from the linear constrainst in the problem. This can be used in some cuts, altough for now we don't really exploit it.
optional bool detect_linearized_product = 277 [default = false];- Returns:
- This builder for chaining.
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hasUseNewIntegerConflictResolution
public boolean hasUseNewIntegerConflictResolution()This should be better on integer problems. But it is still work in progress.
optional bool use_new_integer_conflict_resolution = 336 [default = false];- Specified by:
hasUseNewIntegerConflictResolutionin interfaceSatParametersOrBuilder- Returns:
- Whether the useNewIntegerConflictResolution field is set.
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getUseNewIntegerConflictResolution
public boolean getUseNewIntegerConflictResolution()This should be better on integer problems. But it is still work in progress.
optional bool use_new_integer_conflict_resolution = 336 [default = false];- Specified by:
getUseNewIntegerConflictResolutionin interfaceSatParametersOrBuilder- Returns:
- The useNewIntegerConflictResolution.
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setUseNewIntegerConflictResolution
This should be better on integer problems. But it is still work in progress.
optional bool use_new_integer_conflict_resolution = 336 [default = false];- Parameters:
value- The useNewIntegerConflictResolution to set.- Returns:
- This builder for chaining.
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clearUseNewIntegerConflictResolution
This should be better on integer problems. But it is still work in progress.
optional bool use_new_integer_conflict_resolution = 336 [default = false];- Returns:
- This builder for chaining.
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hasCreate1UipBooleanDuringIcr
public boolean hasCreate1UipBooleanDuringIcr()If true, and during integer conflict resolution (icr) the 1-UIP is an integer literal for which we do not have an associated Boolean. Create one.
optional bool create_1uip_boolean_during_icr = 341 [default = true];- Specified by:
hasCreate1UipBooleanDuringIcrin interfaceSatParametersOrBuilder- Returns:
- Whether the create1uipBooleanDuringIcr field is set.
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getCreate1UipBooleanDuringIcr
public boolean getCreate1UipBooleanDuringIcr()If true, and during integer conflict resolution (icr) the 1-UIP is an integer literal for which we do not have an associated Boolean. Create one.
optional bool create_1uip_boolean_during_icr = 341 [default = true];- Specified by:
getCreate1UipBooleanDuringIcrin interfaceSatParametersOrBuilder- Returns:
- The create1uipBooleanDuringIcr.
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setCreate1UipBooleanDuringIcr
If true, and during integer conflict resolution (icr) the 1-UIP is an integer literal for which we do not have an associated Boolean. Create one.
optional bool create_1uip_boolean_during_icr = 341 [default = true];- Parameters:
value- The create1uipBooleanDuringIcr to set.- Returns:
- This builder for chaining.
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clearCreate1UipBooleanDuringIcr
If true, and during integer conflict resolution (icr) the 1-UIP is an integer literal for which we do not have an associated Boolean. Create one.
optional bool create_1uip_boolean_during_icr = 341 [default = true];- Returns:
- This builder for chaining.
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hasMipMaxBound
public boolean hasMipMaxBound()We need to bound the maximum magnitude of the variables for CP-SAT, and that is the bound we use. If the MIP model expect larger variable value in the solution, then the converted model will likely not be relevant.
optional double mip_max_bound = 124 [default = 10000000];- Specified by:
hasMipMaxBoundin interfaceSatParametersOrBuilder- Returns:
- Whether the mipMaxBound field is set.
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getMipMaxBound
public double getMipMaxBound()We need to bound the maximum magnitude of the variables for CP-SAT, and that is the bound we use. If the MIP model expect larger variable value in the solution, then the converted model will likely not be relevant.
optional double mip_max_bound = 124 [default = 10000000];- Specified by:
getMipMaxBoundin interfaceSatParametersOrBuilder- Returns:
- The mipMaxBound.
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setMipMaxBound
We need to bound the maximum magnitude of the variables for CP-SAT, and that is the bound we use. If the MIP model expect larger variable value in the solution, then the converted model will likely not be relevant.
optional double mip_max_bound = 124 [default = 10000000];- Parameters:
value- The mipMaxBound to set.- Returns:
- This builder for chaining.
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clearMipMaxBound
We need to bound the maximum magnitude of the variables for CP-SAT, and that is the bound we use. If the MIP model expect larger variable value in the solution, then the converted model will likely not be relevant.
optional double mip_max_bound = 124 [default = 10000000];- Returns:
- This builder for chaining.
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hasMipVarScaling
public boolean hasMipVarScaling()All continuous variable of the problem will be multiplied by this factor. By default, we don't do any variable scaling and rely on the MIP model to specify continuous variable domain with the wanted precision.
optional double mip_var_scaling = 125 [default = 1];- Specified by:
hasMipVarScalingin interfaceSatParametersOrBuilder- Returns:
- Whether the mipVarScaling field is set.
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getMipVarScaling
public double getMipVarScaling()All continuous variable of the problem will be multiplied by this factor. By default, we don't do any variable scaling and rely on the MIP model to specify continuous variable domain with the wanted precision.
optional double mip_var_scaling = 125 [default = 1];- Specified by:
getMipVarScalingin interfaceSatParametersOrBuilder- Returns:
- The mipVarScaling.
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setMipVarScaling
All continuous variable of the problem will be multiplied by this factor. By default, we don't do any variable scaling and rely on the MIP model to specify continuous variable domain with the wanted precision.
optional double mip_var_scaling = 125 [default = 1];- Parameters:
value- The mipVarScaling to set.- Returns:
- This builder for chaining.
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clearMipVarScaling
All continuous variable of the problem will be multiplied by this factor. By default, we don't do any variable scaling and rely on the MIP model to specify continuous variable domain with the wanted precision.
optional double mip_var_scaling = 125 [default = 1];- Returns:
- This builder for chaining.
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hasMipScaleLargeDomain
public boolean hasMipScaleLargeDomain()If this is false, then mip_var_scaling is only applied to variables with "small" domain. If it is true, we scale all floating point variable independenlty of their domain.
optional bool mip_scale_large_domain = 225 [default = false];- Specified by:
hasMipScaleLargeDomainin interfaceSatParametersOrBuilder- Returns:
- Whether the mipScaleLargeDomain field is set.
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getMipScaleLargeDomain
public boolean getMipScaleLargeDomain()If this is false, then mip_var_scaling is only applied to variables with "small" domain. If it is true, we scale all floating point variable independenlty of their domain.
optional bool mip_scale_large_domain = 225 [default = false];- Specified by:
getMipScaleLargeDomainin interfaceSatParametersOrBuilder- Returns:
- The mipScaleLargeDomain.
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setMipScaleLargeDomain
If this is false, then mip_var_scaling is only applied to variables with "small" domain. If it is true, we scale all floating point variable independenlty of their domain.
optional bool mip_scale_large_domain = 225 [default = false];- Parameters:
value- The mipScaleLargeDomain to set.- Returns:
- This builder for chaining.
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clearMipScaleLargeDomain
If this is false, then mip_var_scaling is only applied to variables with "small" domain. If it is true, we scale all floating point variable independenlty of their domain.
optional bool mip_scale_large_domain = 225 [default = false];- Returns:
- This builder for chaining.
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hasMipAutomaticallyScaleVariables
public boolean hasMipAutomaticallyScaleVariables()If true, some continuous variable might be automatically scaled. For now, this is only the case where we detect that a variable is actually an integer multiple of a constant. For instance, variables of the form k * 0.5 are quite frequent, and if we detect this, we will scale such variable domain by 2 to make it implied integer.
optional bool mip_automatically_scale_variables = 166 [default = true];- Specified by:
hasMipAutomaticallyScaleVariablesin interfaceSatParametersOrBuilder- Returns:
- Whether the mipAutomaticallyScaleVariables field is set.
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getMipAutomaticallyScaleVariables
public boolean getMipAutomaticallyScaleVariables()If true, some continuous variable might be automatically scaled. For now, this is only the case where we detect that a variable is actually an integer multiple of a constant. For instance, variables of the form k * 0.5 are quite frequent, and if we detect this, we will scale such variable domain by 2 to make it implied integer.
optional bool mip_automatically_scale_variables = 166 [default = true];- Specified by:
getMipAutomaticallyScaleVariablesin interfaceSatParametersOrBuilder- Returns:
- The mipAutomaticallyScaleVariables.
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setMipAutomaticallyScaleVariables
If true, some continuous variable might be automatically scaled. For now, this is only the case where we detect that a variable is actually an integer multiple of a constant. For instance, variables of the form k * 0.5 are quite frequent, and if we detect this, we will scale such variable domain by 2 to make it implied integer.
optional bool mip_automatically_scale_variables = 166 [default = true];- Parameters:
value- The mipAutomaticallyScaleVariables to set.- Returns:
- This builder for chaining.
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clearMipAutomaticallyScaleVariables
If true, some continuous variable might be automatically scaled. For now, this is only the case where we detect that a variable is actually an integer multiple of a constant. For instance, variables of the form k * 0.5 are quite frequent, and if we detect this, we will scale such variable domain by 2 to make it implied integer.
optional bool mip_automatically_scale_variables = 166 [default = true];- Returns:
- This builder for chaining.
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hasOnlySolveIp
public boolean hasOnlySolveIp()If one try to solve a MIP model with CP-SAT, because we assume all variable to be integer after scaling, we will not necessarily have the correct optimal. Note however that all feasible solutions are valid since we will just solve a more restricted version of the original problem. This parameters is here to prevent user to think the solution is optimal when it might not be. One will need to manually set this to false to solve a MIP model where the optimal might be different. Note that this is tested after some MIP presolve steps, so even if not all original variable are integer, we might end up with a pure IP after presolve and after implied integer detection.
optional bool only_solve_ip = 222 [default = false];- Specified by:
hasOnlySolveIpin interfaceSatParametersOrBuilder- Returns:
- Whether the onlySolveIp field is set.
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getOnlySolveIp
public boolean getOnlySolveIp()If one try to solve a MIP model with CP-SAT, because we assume all variable to be integer after scaling, we will not necessarily have the correct optimal. Note however that all feasible solutions are valid since we will just solve a more restricted version of the original problem. This parameters is here to prevent user to think the solution is optimal when it might not be. One will need to manually set this to false to solve a MIP model where the optimal might be different. Note that this is tested after some MIP presolve steps, so even if not all original variable are integer, we might end up with a pure IP after presolve and after implied integer detection.
optional bool only_solve_ip = 222 [default = false];- Specified by:
getOnlySolveIpin interfaceSatParametersOrBuilder- Returns:
- The onlySolveIp.
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setOnlySolveIp
If one try to solve a MIP model with CP-SAT, because we assume all variable to be integer after scaling, we will not necessarily have the correct optimal. Note however that all feasible solutions are valid since we will just solve a more restricted version of the original problem. This parameters is here to prevent user to think the solution is optimal when it might not be. One will need to manually set this to false to solve a MIP model where the optimal might be different. Note that this is tested after some MIP presolve steps, so even if not all original variable are integer, we might end up with a pure IP after presolve and after implied integer detection.
optional bool only_solve_ip = 222 [default = false];- Parameters:
value- The onlySolveIp to set.- Returns:
- This builder for chaining.
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clearOnlySolveIp
If one try to solve a MIP model with CP-SAT, because we assume all variable to be integer after scaling, we will not necessarily have the correct optimal. Note however that all feasible solutions are valid since we will just solve a more restricted version of the original problem. This parameters is here to prevent user to think the solution is optimal when it might not be. One will need to manually set this to false to solve a MIP model where the optimal might be different. Note that this is tested after some MIP presolve steps, so even if not all original variable are integer, we might end up with a pure IP after presolve and after implied integer detection.
optional bool only_solve_ip = 222 [default = false];- Returns:
- This builder for chaining.
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hasMipWantedPrecision
public boolean hasMipWantedPrecision()When scaling constraint with double coefficients to integer coefficients, we will multiply by a power of 2 and round the coefficients. We will choose the lowest power such that we have no potential overflow (see mip_max_activity_exponent) and the worst case constraint activity error does not exceed this threshold. Note that we also detect constraint with rational coefficients and scale them accordingly when it seems better instead of using a power of 2. We also relax all constraint bounds by this absolute value. For pure integer constraint, if this value if lower than one, this will not change anything. However it is needed when scaling MIP problems. If we manage to scale a constraint correctly, the maximum error we can make will be twice this value (once for the scaling error and once for the relaxed bounds). If we are not able to scale that well, we will display that fact but still scale as best as we can.
optional double mip_wanted_precision = 126 [default = 1e-06];- Specified by:
hasMipWantedPrecisionin interfaceSatParametersOrBuilder- Returns:
- Whether the mipWantedPrecision field is set.
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getMipWantedPrecision
public double getMipWantedPrecision()When scaling constraint with double coefficients to integer coefficients, we will multiply by a power of 2 and round the coefficients. We will choose the lowest power such that we have no potential overflow (see mip_max_activity_exponent) and the worst case constraint activity error does not exceed this threshold. Note that we also detect constraint with rational coefficients and scale them accordingly when it seems better instead of using a power of 2. We also relax all constraint bounds by this absolute value. For pure integer constraint, if this value if lower than one, this will not change anything. However it is needed when scaling MIP problems. If we manage to scale a constraint correctly, the maximum error we can make will be twice this value (once for the scaling error and once for the relaxed bounds). If we are not able to scale that well, we will display that fact but still scale as best as we can.
optional double mip_wanted_precision = 126 [default = 1e-06];- Specified by:
getMipWantedPrecisionin interfaceSatParametersOrBuilder- Returns:
- The mipWantedPrecision.
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setMipWantedPrecision
When scaling constraint with double coefficients to integer coefficients, we will multiply by a power of 2 and round the coefficients. We will choose the lowest power such that we have no potential overflow (see mip_max_activity_exponent) and the worst case constraint activity error does not exceed this threshold. Note that we also detect constraint with rational coefficients and scale them accordingly when it seems better instead of using a power of 2. We also relax all constraint bounds by this absolute value. For pure integer constraint, if this value if lower than one, this will not change anything. However it is needed when scaling MIP problems. If we manage to scale a constraint correctly, the maximum error we can make will be twice this value (once for the scaling error and once for the relaxed bounds). If we are not able to scale that well, we will display that fact but still scale as best as we can.
optional double mip_wanted_precision = 126 [default = 1e-06];- Parameters:
value- The mipWantedPrecision to set.- Returns:
- This builder for chaining.
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clearMipWantedPrecision
When scaling constraint with double coefficients to integer coefficients, we will multiply by a power of 2 and round the coefficients. We will choose the lowest power such that we have no potential overflow (see mip_max_activity_exponent) and the worst case constraint activity error does not exceed this threshold. Note that we also detect constraint with rational coefficients and scale them accordingly when it seems better instead of using a power of 2. We also relax all constraint bounds by this absolute value. For pure integer constraint, if this value if lower than one, this will not change anything. However it is needed when scaling MIP problems. If we manage to scale a constraint correctly, the maximum error we can make will be twice this value (once for the scaling error and once for the relaxed bounds). If we are not able to scale that well, we will display that fact but still scale as best as we can.
optional double mip_wanted_precision = 126 [default = 1e-06];- Returns:
- This builder for chaining.
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hasMipMaxActivityExponent
public boolean hasMipMaxActivityExponent()To avoid integer overflow, we always force the maximum possible constraint activity (and objective value) according to the initial variable domain to be smaller than 2 to this given power. Because of this, we cannot always reach the "mip_wanted_precision" parameter above. This can go as high as 62, but some internal algo currently abort early if they might run into integer overflow, so it is better to keep it a bit lower than this.
optional int32 mip_max_activity_exponent = 127 [default = 53];- Specified by:
hasMipMaxActivityExponentin interfaceSatParametersOrBuilder- Returns:
- Whether the mipMaxActivityExponent field is set.
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getMipMaxActivityExponent
public int getMipMaxActivityExponent()To avoid integer overflow, we always force the maximum possible constraint activity (and objective value) according to the initial variable domain to be smaller than 2 to this given power. Because of this, we cannot always reach the "mip_wanted_precision" parameter above. This can go as high as 62, but some internal algo currently abort early if they might run into integer overflow, so it is better to keep it a bit lower than this.
optional int32 mip_max_activity_exponent = 127 [default = 53];- Specified by:
getMipMaxActivityExponentin interfaceSatParametersOrBuilder- Returns:
- The mipMaxActivityExponent.
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setMipMaxActivityExponent
To avoid integer overflow, we always force the maximum possible constraint activity (and objective value) according to the initial variable domain to be smaller than 2 to this given power. Because of this, we cannot always reach the "mip_wanted_precision" parameter above. This can go as high as 62, but some internal algo currently abort early if they might run into integer overflow, so it is better to keep it a bit lower than this.
optional int32 mip_max_activity_exponent = 127 [default = 53];- Parameters:
value- The mipMaxActivityExponent to set.- Returns:
- This builder for chaining.
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clearMipMaxActivityExponent
To avoid integer overflow, we always force the maximum possible constraint activity (and objective value) according to the initial variable domain to be smaller than 2 to this given power. Because of this, we cannot always reach the "mip_wanted_precision" parameter above. This can go as high as 62, but some internal algo currently abort early if they might run into integer overflow, so it is better to keep it a bit lower than this.
optional int32 mip_max_activity_exponent = 127 [default = 53];- Returns:
- This builder for chaining.
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hasMipCheckPrecision
public boolean hasMipCheckPrecision()As explained in mip_precision and mip_max_activity_exponent, we cannot always reach the wanted precision during scaling. We use this threshold to enphasize in the logs when the precision seems bad.
optional double mip_check_precision = 128 [default = 0.0001];- Specified by:
hasMipCheckPrecisionin interfaceSatParametersOrBuilder- Returns:
- Whether the mipCheckPrecision field is set.
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getMipCheckPrecision
public double getMipCheckPrecision()As explained in mip_precision and mip_max_activity_exponent, we cannot always reach the wanted precision during scaling. We use this threshold to enphasize in the logs when the precision seems bad.
optional double mip_check_precision = 128 [default = 0.0001];- Specified by:
getMipCheckPrecisionin interfaceSatParametersOrBuilder- Returns:
- The mipCheckPrecision.
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setMipCheckPrecision
As explained in mip_precision and mip_max_activity_exponent, we cannot always reach the wanted precision during scaling. We use this threshold to enphasize in the logs when the precision seems bad.
optional double mip_check_precision = 128 [default = 0.0001];- Parameters:
value- The mipCheckPrecision to set.- Returns:
- This builder for chaining.
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clearMipCheckPrecision
As explained in mip_precision and mip_max_activity_exponent, we cannot always reach the wanted precision during scaling. We use this threshold to enphasize in the logs when the precision seems bad.
optional double mip_check_precision = 128 [default = 0.0001];- Returns:
- This builder for chaining.
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hasMipComputeTrueObjectiveBound
public boolean hasMipComputeTrueObjectiveBound()Even if we make big error when scaling the objective, we can always derive a correct lower bound on the original objective by using the exact lower bound on the scaled integer version of the objective. This should be fast, but if you don't care about having a precise lower bound, you can turn it off.
optional bool mip_compute_true_objective_bound = 198 [default = true];- Specified by:
hasMipComputeTrueObjectiveBoundin interfaceSatParametersOrBuilder- Returns:
- Whether the mipComputeTrueObjectiveBound field is set.
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getMipComputeTrueObjectiveBound
public boolean getMipComputeTrueObjectiveBound()Even if we make big error when scaling the objective, we can always derive a correct lower bound on the original objective by using the exact lower bound on the scaled integer version of the objective. This should be fast, but if you don't care about having a precise lower bound, you can turn it off.
optional bool mip_compute_true_objective_bound = 198 [default = true];- Specified by:
getMipComputeTrueObjectiveBoundin interfaceSatParametersOrBuilder- Returns:
- The mipComputeTrueObjectiveBound.
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setMipComputeTrueObjectiveBound
Even if we make big error when scaling the objective, we can always derive a correct lower bound on the original objective by using the exact lower bound on the scaled integer version of the objective. This should be fast, but if you don't care about having a precise lower bound, you can turn it off.
optional bool mip_compute_true_objective_bound = 198 [default = true];- Parameters:
value- The mipComputeTrueObjectiveBound to set.- Returns:
- This builder for chaining.
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clearMipComputeTrueObjectiveBound
Even if we make big error when scaling the objective, we can always derive a correct lower bound on the original objective by using the exact lower bound on the scaled integer version of the objective. This should be fast, but if you don't care about having a precise lower bound, you can turn it off.
optional bool mip_compute_true_objective_bound = 198 [default = true];- Returns:
- This builder for chaining.
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hasMipMaxValidMagnitude
public boolean hasMipMaxValidMagnitude()Any finite values in the input MIP must be below this threshold, otherwise the model will be reported invalid. This is needed to avoid floating point overflow when evaluating bounds * coeff for instance. We are a bit more defensive, but in practice, users shouldn't use super large values in a MIP.
optional double mip_max_valid_magnitude = 199 [default = 1e+20];- Specified by:
hasMipMaxValidMagnitudein interfaceSatParametersOrBuilder- Returns:
- Whether the mipMaxValidMagnitude field is set.
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getMipMaxValidMagnitude
public double getMipMaxValidMagnitude()Any finite values in the input MIP must be below this threshold, otherwise the model will be reported invalid. This is needed to avoid floating point overflow when evaluating bounds * coeff for instance. We are a bit more defensive, but in practice, users shouldn't use super large values in a MIP.
optional double mip_max_valid_magnitude = 199 [default = 1e+20];- Specified by:
getMipMaxValidMagnitudein interfaceSatParametersOrBuilder- Returns:
- The mipMaxValidMagnitude.
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setMipMaxValidMagnitude
Any finite values in the input MIP must be below this threshold, otherwise the model will be reported invalid. This is needed to avoid floating point overflow when evaluating bounds * coeff for instance. We are a bit more defensive, but in practice, users shouldn't use super large values in a MIP.
optional double mip_max_valid_magnitude = 199 [default = 1e+20];- Parameters:
value- The mipMaxValidMagnitude to set.- Returns:
- This builder for chaining.
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clearMipMaxValidMagnitude
Any finite values in the input MIP must be below this threshold, otherwise the model will be reported invalid. This is needed to avoid floating point overflow when evaluating bounds * coeff for instance. We are a bit more defensive, but in practice, users shouldn't use super large values in a MIP.
optional double mip_max_valid_magnitude = 199 [default = 1e+20];- Returns:
- This builder for chaining.
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hasMipTreatHighMagnitudeBoundsAsInfinity
public boolean hasMipTreatHighMagnitudeBoundsAsInfinity()By default, any variable/constraint bound with a finite value and a magnitude greater than the mip_max_valid_magnitude will result with a invalid model. This flags change the behavior such that such bounds are silently transformed to +∞ or -∞. It is recommended to keep it at false, and create valid bounds.
optional bool mip_treat_high_magnitude_bounds_as_infinity = 278 [default = false];- Specified by:
hasMipTreatHighMagnitudeBoundsAsInfinityin interfaceSatParametersOrBuilder- Returns:
- Whether the mipTreatHighMagnitudeBoundsAsInfinity field is set.
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getMipTreatHighMagnitudeBoundsAsInfinity
public boolean getMipTreatHighMagnitudeBoundsAsInfinity()By default, any variable/constraint bound with a finite value and a magnitude greater than the mip_max_valid_magnitude will result with a invalid model. This flags change the behavior such that such bounds are silently transformed to +∞ or -∞. It is recommended to keep it at false, and create valid bounds.
optional bool mip_treat_high_magnitude_bounds_as_infinity = 278 [default = false];- Specified by:
getMipTreatHighMagnitudeBoundsAsInfinityin interfaceSatParametersOrBuilder- Returns:
- The mipTreatHighMagnitudeBoundsAsInfinity.
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setMipTreatHighMagnitudeBoundsAsInfinity
By default, any variable/constraint bound with a finite value and a magnitude greater than the mip_max_valid_magnitude will result with a invalid model. This flags change the behavior such that such bounds are silently transformed to +∞ or -∞. It is recommended to keep it at false, and create valid bounds.
optional bool mip_treat_high_magnitude_bounds_as_infinity = 278 [default = false];- Parameters:
value- The mipTreatHighMagnitudeBoundsAsInfinity to set.- Returns:
- This builder for chaining.
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clearMipTreatHighMagnitudeBoundsAsInfinity
By default, any variable/constraint bound with a finite value and a magnitude greater than the mip_max_valid_magnitude will result with a invalid model. This flags change the behavior such that such bounds are silently transformed to +∞ or -∞. It is recommended to keep it at false, and create valid bounds.
optional bool mip_treat_high_magnitude_bounds_as_infinity = 278 [default = false];- Returns:
- This builder for chaining.
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hasMipDropTolerance
public boolean hasMipDropTolerance()Any value in the input mip with a magnitude lower than this will be set to zero. This is to avoid some issue in LP presolving.
optional double mip_drop_tolerance = 232 [default = 1e-16];- Specified by:
hasMipDropTolerancein interfaceSatParametersOrBuilder- Returns:
- Whether the mipDropTolerance field is set.
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getMipDropTolerance
public double getMipDropTolerance()Any value in the input mip with a magnitude lower than this will be set to zero. This is to avoid some issue in LP presolving.
optional double mip_drop_tolerance = 232 [default = 1e-16];- Specified by:
getMipDropTolerancein interfaceSatParametersOrBuilder- Returns:
- The mipDropTolerance.
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setMipDropTolerance
Any value in the input mip with a magnitude lower than this will be set to zero. This is to avoid some issue in LP presolving.
optional double mip_drop_tolerance = 232 [default = 1e-16];- Parameters:
value- The mipDropTolerance to set.- Returns:
- This builder for chaining.
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clearMipDropTolerance
Any value in the input mip with a magnitude lower than this will be set to zero. This is to avoid some issue in LP presolving.
optional double mip_drop_tolerance = 232 [default = 1e-16];- Returns:
- This builder for chaining.
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hasMipPresolveLevel
public boolean hasMipPresolveLevel()When solving a MIP, we do some basic floating point presolving before scaling the problem to integer to be handled by CP-SAT. This control how much of that presolve we do. It can help to better scale floating point model, but it is not always behaving nicely.
optional int32 mip_presolve_level = 261 [default = 2];- Specified by:
hasMipPresolveLevelin interfaceSatParametersOrBuilder- Returns:
- Whether the mipPresolveLevel field is set.
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getMipPresolveLevel
public int getMipPresolveLevel()When solving a MIP, we do some basic floating point presolving before scaling the problem to integer to be handled by CP-SAT. This control how much of that presolve we do. It can help to better scale floating point model, but it is not always behaving nicely.
optional int32 mip_presolve_level = 261 [default = 2];- Specified by:
getMipPresolveLevelin interfaceSatParametersOrBuilder- Returns:
- The mipPresolveLevel.
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setMipPresolveLevel
When solving a MIP, we do some basic floating point presolving before scaling the problem to integer to be handled by CP-SAT. This control how much of that presolve we do. It can help to better scale floating point model, but it is not always behaving nicely.
optional int32 mip_presolve_level = 261 [default = 2];- Parameters:
value- The mipPresolveLevel to set.- Returns:
- This builder for chaining.
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clearMipPresolveLevel
When solving a MIP, we do some basic floating point presolving before scaling the problem to integer to be handled by CP-SAT. This control how much of that presolve we do. It can help to better scale floating point model, but it is not always behaving nicely.
optional int32 mip_presolve_level = 261 [default = 2];- Returns:
- This builder for chaining.
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