![]() |
Google OR-Tools v9.14
a fast and portable software suite for combinatorial optimization
|
Parameters for PrimalDualHybridGradient() in primal_dual_hybrid_gradient.h. While the defaults are generally good, it is usually worthwhile to perform a parameter sweep to find good settings for a particular family of problems. The following parameters should be considered for tuning: - restart_strategy (jointly with major_iteration_frequency) - primal_weight_update_smoothing (jointly with initial_primal_weight) - presolve_options.use_glop - l_inf_ruiz_iterations - l2_norm_rescaling In addition, tune num_threads to speed up the solve.
Protobuf type operations_research.pdlp.PrimalDualHybridGradientParams
Definition at line 25 of file PrimalDualHybridGradientParams.java.
Classes | |
class | Builder |
enum | LinesearchRule |
class | PresolveOptions |
interface | PresolveOptionsOrBuilder |
enum | RestartStrategy |
Static Public Member Functions | |
static final com.google.protobuf.Descriptors.Descriptor | getDescriptor () |
static com.google.ortools.pdlp.PrimalDualHybridGradientParams | parseFrom (java.nio.ByteBuffer data) throws com.google.protobuf.InvalidProtocolBufferException |
static com.google.ortools.pdlp.PrimalDualHybridGradientParams | parseFrom (java.nio.ByteBuffer data, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws com.google.protobuf.InvalidProtocolBufferException |
static com.google.ortools.pdlp.PrimalDualHybridGradientParams | parseFrom (com.google.protobuf.ByteString data) throws com.google.protobuf.InvalidProtocolBufferException |
static com.google.ortools.pdlp.PrimalDualHybridGradientParams | parseFrom (com.google.protobuf.ByteString data, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws com.google.protobuf.InvalidProtocolBufferException |
static com.google.ortools.pdlp.PrimalDualHybridGradientParams | parseFrom (byte[] data) throws com.google.protobuf.InvalidProtocolBufferException |
static com.google.ortools.pdlp.PrimalDualHybridGradientParams | parseFrom (byte[] data, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws com.google.protobuf.InvalidProtocolBufferException |
static com.google.ortools.pdlp.PrimalDualHybridGradientParams | parseFrom (java.io.InputStream input) throws java.io.IOException |
static com.google.ortools.pdlp.PrimalDualHybridGradientParams | parseFrom (java.io.InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws java.io.IOException |
static com.google.ortools.pdlp.PrimalDualHybridGradientParams | parseDelimitedFrom (java.io.InputStream input) throws java.io.IOException |
static com.google.ortools.pdlp.PrimalDualHybridGradientParams | parseDelimitedFrom (java.io.InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws java.io.IOException |
static com.google.ortools.pdlp.PrimalDualHybridGradientParams | parseFrom (com.google.protobuf.CodedInputStream input) throws java.io.IOException |
static com.google.ortools.pdlp.PrimalDualHybridGradientParams | parseFrom (com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws java.io.IOException |
static Builder | newBuilder () |
static Builder | newBuilder (com.google.ortools.pdlp.PrimalDualHybridGradientParams prototype) |
static com.google.ortools.pdlp.PrimalDualHybridGradientParams | getDefaultInstance () |
static com.google.protobuf.Parser< PrimalDualHybridGradientParams > | parser () |
Protected Member Functions | |
com.google.protobuf.GeneratedMessage.FieldAccessorTable | internalGetFieldAccessorTable () |
Builder | newBuilderForType (com.google.protobuf.GeneratedMessage.BuilderParent parent) |
boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.equals | ( | final java.lang.Object | obj | ) |
Definition at line 2523 of file PrimalDualHybridGradientParams.java.
com.google.ortools.pdlp.AdaptiveLinesearchParams com.google.ortools.pdlp.PrimalDualHybridGradientParams.getAdaptiveLinesearchParameters | ( | ) |
optional .operations_research.pdlp.AdaptiveLinesearchParams adaptive_linesearch_parameters = 18;
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1872 of file PrimalDualHybridGradientParams.java.
com.google.ortools.pdlp.AdaptiveLinesearchParamsOrBuilder com.google.ortools.pdlp.PrimalDualHybridGradientParams.getAdaptiveLinesearchParametersOrBuilder | ( | ) |
optional .operations_research.pdlp.AdaptiveLinesearchParams adaptive_linesearch_parameters = 18;
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1879 of file PrimalDualHybridGradientParams.java.
boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.getApplyFeasibilityPolishingAfterLimitsReached | ( | ) |
If true, feasibility polishing will be applied after the iteration limit, kkt limit, or time limit is reached. This can result in a solution that is closer to feasibility, at the expense of violating the limit by a moderate amount.
optional bool apply_feasibility_polishing_after_limits_reached = 33 [default = false];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 2241 of file PrimalDualHybridGradientParams.java.
boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.getApplyFeasibilityPolishingIfSolverIsInterrupted | ( | ) |
If true, feasibility polishing will be applied after the solver is interrupted. This can result in a solution that is closer to feasibility, at the expense of not stopping as promptly when interrupted.
optional bool apply_feasibility_polishing_if_solver_is_interrupted = 34 [default = false];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 2272 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 5927 of file PrimalDualHybridGradientParams.java.
com.google.ortools.pdlp.PrimalDualHybridGradientParams com.google.ortools.pdlp.PrimalDualHybridGradientParams.getDefaultInstanceForType | ( | ) |
Definition at line 5963 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 63 of file PrimalDualHybridGradientParams.java.
double com.google.ortools.pdlp.PrimalDualHybridGradientParams.getDiagonalQpTrustRegionSolverTolerance | ( | ) |
The solve tolerance of the experimental trust region solver for diagonal QPs, controlling the accuracy of binary search over a one-dimensional scaling parameter. Smaller values imply smaller relative error of the final solution vector. TODO(user): Find an expression for the final relative error.
optional double diagonal_qp_trust_region_solver_tolerance = 24 [default = 1e-08];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 2131 of file PrimalDualHybridGradientParams.java.
boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.getHandleSomePrimalGradientsOnFiniteBoundsAsResiduals | ( | ) |
See https://developers.google.com/optimization/lp/pdlp_math#treating_some_variable_bounds_as_infinite for a description of this flag.
optional bool handle_some_primal_gradients_on_finite_bounds_as_residuals = 29 [default = true];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 2059 of file PrimalDualHybridGradientParams.java.
double com.google.ortools.pdlp.PrimalDualHybridGradientParams.getInfiniteConstraintBoundThreshold | ( | ) |
Constraint bounds with absolute value at least this threshold are replaced with infinities. NOTE: This primarily affects the relative convergence criteria. A smaller value makes the relative convergence criteria stronger. It also affects the problem statistics LOG()ed at the start of the run, and the default initial primal weight, since that is based on the norm of the bounds.
optional double infinite_constraint_bound_threshold = 22 [default = inf];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 2028 of file PrimalDualHybridGradientParams.java.
double com.google.ortools.pdlp.PrimalDualHybridGradientParams.getInitialPrimalWeight | ( | ) |
The initial value of the primal weight (i.e., the ratio of primal and dual step sizes). The primal weight remains fixed throughout the solve if primal_weight_update_smoothing = 0.0. If unset, the default is the ratio of the norm of the objective vector to the L2 norm of the combined constraint bounds vector (as defined above). If this ratio is not finite and positive, then the default is 1.0 instead. For tuning, try powers of 10, for example, from 10^{-6} to 10^6.
optional double initial_primal_weight = 8;
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1675 of file PrimalDualHybridGradientParams.java.
double com.google.ortools.pdlp.PrimalDualHybridGradientParams.getInitialStepSizeScaling | ( | ) |
Scaling factor applied to the initial step size (all step sizes if linesearch_rule == CONSTANT_STEP_SIZE_RULE).
optional double initial_step_size_scaling = 25 [default = 1];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1934 of file PrimalDualHybridGradientParams.java.
boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.getL2NormRescaling | ( | ) |
If true, applies L_2 norm rescaling after the Ruiz rescaling. Heuristically this has been found to help convergence.
optional bool l2_norm_rescaling = 10 [default = true];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1761 of file PrimalDualHybridGradientParams.java.
com.google.ortools.pdlp.PrimalDualHybridGradientParams.LinesearchRule com.google.ortools.pdlp.PrimalDualHybridGradientParams.getLinesearchRule | ( | ) |
Linesearch rule applied at each major iteration.
optional .operations_research.pdlp.PrimalDualHybridGradientParams.LinesearchRule linesearch_rule = 12 [default = ADAPTIVE_LINESEARCH_RULE];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1852 of file PrimalDualHybridGradientParams.java.
int com.google.ortools.pdlp.PrimalDualHybridGradientParams.getLInfRuizIterations | ( | ) |
Number of L_infinity Ruiz rescaling iterations to apply to the constraint matrix. Zero disables this rescaling pass. Recommended values to try when tuning are 0, 5, and 10.
optional int32 l_inf_ruiz_iterations = 9 [default = 5];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1732 of file PrimalDualHybridGradientParams.java.
double com.google.ortools.pdlp.PrimalDualHybridGradientParams.getLogIntervalSeconds | ( | ) |
Time between iteration-level statistics logging (if `verbosity_level > 1`). Since iteration-level statistics are only generated when performing termination checks, logs will be generated from next termination check after `log_interval_seconds` have elapsed. Should be >= 0.0. 0.0 (the default) means log statistics at every termination check.
optional double log_interval_seconds = 31 [default = 0];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1497 of file PrimalDualHybridGradientParams.java.
int com.google.ortools.pdlp.PrimalDualHybridGradientParams.getMajorIterationFrequency | ( | ) |
The frequency at which extra work is performed to make major algorithmic decisions, e.g., performing restarts and updating the primal weight. Major iterations also trigger a termination check. For best performance using the NO_RESTARTS or EVERY_MAJOR_ITERATION rule, one should perform a log-scale grid search over this parameter, for example, over powers of two. ADAPTIVE_HEURISTIC is mostly insensitive to this value.
optional int32 major_iteration_frequency = 4 [default = 64];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1534 of file PrimalDualHybridGradientParams.java.
com.google.ortools.pdlp.MalitskyPockParams com.google.ortools.pdlp.PrimalDualHybridGradientParams.getMalitskyPockParameters | ( | ) |
optional .operations_research.pdlp.MalitskyPockParams malitsky_pock_parameters = 19;
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1898 of file PrimalDualHybridGradientParams.java.
com.google.ortools.pdlp.MalitskyPockParamsOrBuilder com.google.ortools.pdlp.PrimalDualHybridGradientParams.getMalitskyPockParametersOrBuilder | ( | ) |
optional .operations_research.pdlp.MalitskyPockParams malitsky_pock_parameters = 19;
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1905 of file PrimalDualHybridGradientParams.java.
double com.google.ortools.pdlp.PrimalDualHybridGradientParams.getNecessaryReductionForRestart | ( | ) |
For ADAPTIVE_HEURISTIC only: A relative reduction in the potential function by this amount triggers a restart if, additionally, the quality of the iterates appears to be getting worse. The value must be in the interval [sufficient_reduction_for_restart, 1). Smaller values make restarts less frequent, and larger values make them more frequent.
optional double necessary_reduction_for_restart = 17 [default = 0.9];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1827 of file PrimalDualHybridGradientParams.java.
int com.google.ortools.pdlp.PrimalDualHybridGradientParams.getNumShards | ( | ) |
For more efficient parallel computation, the matrices and vectors are divided (virtually) into num_shards shards. Results are computed independently for each shard and then combined. As a consequence, the order of computation, and hence floating point roundoff, depends on the number of shards so reproducible results require using the same value for num_shards. However, for efficiency num_shards should a be at least num_threads, and preferably at least 4*num_threads to allow better load balancing. If num_shards is positive, the computation will use that many shards. Otherwise a default that depends on num_threads will be used.
optional int32 num_shards = 27 [default = 0];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1354 of file PrimalDualHybridGradientParams.java.
int com.google.ortools.pdlp.PrimalDualHybridGradientParams.getNumThreads | ( | ) |
The number of threads to use. Must be positive. Try various values of num_threads, up to the number of physical cores. Performance may not be monotonically increasing with the number of threads because of memory bandwidth limitations.
optional int32 num_threads = 2 [default = 1];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1311 of file PrimalDualHybridGradientParams.java.
com.google.protobuf.Parser< PrimalDualHybridGradientParams > com.google.ortools.pdlp.PrimalDualHybridGradientParams.getParserForType | ( | ) |
Definition at line 5958 of file PrimalDualHybridGradientParams.java.
com.google.ortools.pdlp.PrimalDualHybridGradientParams.PresolveOptions com.google.ortools.pdlp.PrimalDualHybridGradientParams.getPresolveOptions | ( | ) |
optional .operations_research.pdlp.PrimalDualHybridGradientParams.PresolveOptions presolve_options = 16;
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1694 of file PrimalDualHybridGradientParams.java.
com.google.ortools.pdlp.PrimalDualHybridGradientParams.PresolveOptionsOrBuilder com.google.ortools.pdlp.PrimalDualHybridGradientParams.getPresolveOptionsOrBuilder | ( | ) |
optional .operations_research.pdlp.PrimalDualHybridGradientParams.PresolveOptions presolve_options = 16;
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1701 of file PrimalDualHybridGradientParams.java.
double com.google.ortools.pdlp.PrimalDualHybridGradientParams.getPrimalWeightUpdateSmoothing | ( | ) |
This parameter controls exponential smoothing of log(primal_weight) when a primal weight update occurs (i.e., when the ratio of primal and dual step sizes is adjusted). At 0.0, the primal weight will be frozen at its initial value and there will be no dynamic updates in the algorithm. At 1.0, there is no smoothing in the updates. The default of 0.5 generally performs well, but has been observed on occasion to trigger unstable swings in the primal weight. We recommend also trying 0.0 (disabling primal weight updates), in which case you must also tune initial_primal_weight.
optional double primal_weight_update_smoothing = 7 [default = 0.5];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1636 of file PrimalDualHybridGradientParams.java.
int com.google.ortools.pdlp.PrimalDualHybridGradientParams.getRandomProjectionSeeds | ( | int | index | ) |
Seeds for generating (pseudo-)random projections of iterates during termination checks. For each seed, the projection of the primal and dual solutions onto random planes in primal and dual space will be computed and added the IterationStats if record_iteration_stats is true. The random planes generated will be determined by the seeds, the primal and dual dimensions, and num_threads.
repeated int32 random_projection_seeds = 28 [packed = true];
index | The index of the element to return. |
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1990 of file PrimalDualHybridGradientParams.java.
int com.google.ortools.pdlp.PrimalDualHybridGradientParams.getRandomProjectionSeedsCount | ( | ) |
Seeds for generating (pseudo-)random projections of iterates during termination checks. For each seed, the projection of the primal and dual solutions onto random planes in primal and dual space will be computed and added the IterationStats if record_iteration_stats is true. The random planes generated will be determined by the seeds, the primal and dual dimensions, and num_threads.
repeated int32 random_projection_seeds = 28 [packed = true];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1973 of file PrimalDualHybridGradientParams.java.
java.util.List< java.lang.Integer > com.google.ortools.pdlp.PrimalDualHybridGradientParams.getRandomProjectionSeedsList | ( | ) |
Seeds for generating (pseudo-)random projections of iterates during termination checks. For each seed, the projection of the primal and dual solutions onto random planes in primal and dual space will be computed and added the IterationStats if record_iteration_stats is true. The random planes generated will be determined by the seeds, the primal and dual dimensions, and num_threads.
repeated int32 random_projection_seeds = 28 [packed = true];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1957 of file PrimalDualHybridGradientParams.java.
boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.getRecordIterationStats | ( | ) |
If true, the iteration_stats field of the SolveLog output will be populated at every iteration. Note that we only compute solution statistics at termination checks. Setting this parameter to true may substantially increase the size of the output.
optional bool record_iteration_stats = 3;
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1415 of file PrimalDualHybridGradientParams.java.
com.google.ortools.pdlp.PrimalDualHybridGradientParams.RestartStrategy com.google.ortools.pdlp.PrimalDualHybridGradientParams.getRestartStrategy | ( | ) |
NO_RESTARTS and EVERY_MAJOR_ITERATION occasionally outperform the default. If using a strategy other than ADAPTIVE_HEURISTIC, you must also tune major_iteration_frequency.
optional .operations_research.pdlp.PrimalDualHybridGradientParams.RestartStrategy restart_strategy = 6 [default = ADAPTIVE_HEURISTIC];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1594 of file PrimalDualHybridGradientParams.java.
com.google.ortools.pdlp.SchedulerType com.google.ortools.pdlp.PrimalDualHybridGradientParams.getSchedulerType | ( | ) |
The type of scheduler used for CPU multi-threading. See the documentation of the corresponding enum for more details.
optional .operations_research.pdlp.SchedulerType scheduler_type = 32 [default = SCHEDULER_TYPE_GOOGLE_THREADPOOL];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1381 of file PrimalDualHybridGradientParams.java.
int com.google.ortools.pdlp.PrimalDualHybridGradientParams.getSerializedSize | ( | ) |
Definition at line 2386 of file PrimalDualHybridGradientParams.java.
double com.google.ortools.pdlp.PrimalDualHybridGradientParams.getSufficientReductionForRestart | ( | ) |
For ADAPTIVE_HEURISTIC and ADAPTIVE_DISTANCE_BASED only: A relative reduction in the potential function by this amount always triggers a restart. Must be between 0.0 and 1.0.
optional double sufficient_reduction_for_restart = 11 [default = 0.1];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1792 of file PrimalDualHybridGradientParams.java.
int com.google.ortools.pdlp.PrimalDualHybridGradientParams.getTerminationCheckFrequency | ( | ) |
The frequency (based on a counter reset every major iteration) to check for termination (involves extra work) and log iteration stats. Termination checks do not affect algorithmic progress unless termination is triggered.
optional int32 termination_check_frequency = 5 [default = 64];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1565 of file PrimalDualHybridGradientParams.java.
com.google.ortools.pdlp.TerminationCriteria com.google.ortools.pdlp.PrimalDualHybridGradientParams.getTerminationCriteria | ( | ) |
optional .operations_research.pdlp.TerminationCriteria termination_criteria = 1;
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1271 of file PrimalDualHybridGradientParams.java.
com.google.ortools.pdlp.TerminationCriteriaOrBuilder com.google.ortools.pdlp.PrimalDualHybridGradientParams.getTerminationCriteriaOrBuilder | ( | ) |
optional .operations_research.pdlp.TerminationCriteria termination_criteria = 1;
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1278 of file PrimalDualHybridGradientParams.java.
boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.getUseDiagonalQpTrustRegionSolver | ( | ) |
When solving QPs with diagonal objective matrices, this option can be turned on to enable an experimental solver that avoids linearization of the quadratic term. The `diagonal_qp_solver_accuracy` parameter controls the solve accuracy. TODO(user): Turn this option on by default for quadratic programs after numerical evaluation.
optional bool use_diagonal_qp_trust_region_solver = 23 [default = false];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 2096 of file PrimalDualHybridGradientParams.java.
boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.getUseFeasibilityPolishing | ( | ) |
If true, periodically runs feasibility polishing, which attempts to move from latest average iterate to one that is closer to feasibility (i.e., has smaller primal and dual residuals) while probably increasing the objective gap. This is useful primarily when the feasibility tolerances are fairly tight and the objective gap tolerance is somewhat looser. Note that this does not change the termination criteria, but rather can help achieve the termination criteria more quickly when the objective gap is not as important as feasibility. `use_feasibility_polishing` cannot be used with glop presolve, and requires `handle_some_primal_gradients_on_finite_bounds_as_residuals == false`. `use_feasibility_polishing` can only be used with linear programs. Feasibility polishing runs two separate phases, primal feasibility and dual feasibility. The primal feasibility phase runs PDHG on the primal feasibility problem (obtained by changing the objective vector to all zeros), using the average primal iterate and zero dual (which is optimal for the primal feasibility problem) as the initial solution. The dual feasibility phase runs PDHG on the dual feasibility problem (obtained by changing all finite variable and constraint bounds to zero), using the average dual iterate and zero primal (which is optimal for the dual feasibility problem) as the initial solution. The primal solution from the primal feasibility phase and dual solution from the dual feasibility phase are then combined (forming a solution of type `POINT_TYPE_FEASIBILITY_POLISHING_SOLUTION`) and checked against the termination criteria.
optional bool use_feasibility_polishing = 30 [default = false];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 2208 of file PrimalDualHybridGradientParams.java.
int com.google.ortools.pdlp.PrimalDualHybridGradientParams.getVerbosityLevel | ( | ) |
The verbosity of logging. 0: No informational logging. (Errors are logged.) 1: Summary statistics only. No iteration-level details. 2: A table of iteration-level statistics is logged. (See ToShortString() in primal_dual_hybrid_gradient.cc). 3: A more detailed table of iteration-level statistics is logged. (See ToString() in primal_dual_hybrid_gradient.cc). 4: For iteration-level details, prints the statistics of both the average (prefixed with A) and the current iterate (prefixed with C). Also prints internal algorithmic state and details. Logging at levels 2-4 also includes messages from level 1.
optional int32 verbosity_level = 26 [default = 0];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1462 of file PrimalDualHybridGradientParams.java.
boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasAdaptiveLinesearchParameters | ( | ) |
optional .operations_research.pdlp.AdaptiveLinesearchParams adaptive_linesearch_parameters = 18;
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1864 of file PrimalDualHybridGradientParams.java.
boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasApplyFeasibilityPolishingAfterLimitsReached | ( | ) |
If true, feasibility polishing will be applied after the iteration limit, kkt limit, or time limit is reached. This can result in a solution that is closer to feasibility, at the expense of violating the limit by a moderate amount.
optional bool apply_feasibility_polishing_after_limits_reached = 33 [default = false];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 2226 of file PrimalDualHybridGradientParams.java.
boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasApplyFeasibilityPolishingIfSolverIsInterrupted | ( | ) |
If true, feasibility polishing will be applied after the solver is interrupted. This can result in a solution that is closer to feasibility, at the expense of not stopping as promptly when interrupted.
optional bool apply_feasibility_polishing_if_solver_is_interrupted = 34 [default = false];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 2258 of file PrimalDualHybridGradientParams.java.
boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasDiagonalQpTrustRegionSolverTolerance | ( | ) |
The solve tolerance of the experimental trust region solver for diagonal QPs, controlling the accuracy of binary search over a one-dimensional scaling parameter. Smaller values imply smaller relative error of the final solution vector. TODO(user): Find an expression for the final relative error.
optional double diagonal_qp_trust_region_solver_tolerance = 24 [default = 1e-08];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 2115 of file PrimalDualHybridGradientParams.java.
boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasHandleSomePrimalGradientsOnFiniteBoundsAsResiduals | ( | ) |
See https://developers.google.com/optimization/lp/pdlp_math#treating_some_variable_bounds_as_infinite for a description of this flag.
optional bool handle_some_primal_gradients_on_finite_bounds_as_residuals = 29 [default = true];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 2045 of file PrimalDualHybridGradientParams.java.
int com.google.ortools.pdlp.PrimalDualHybridGradientParams.hashCode | ( | ) |
Definition at line 2684 of file PrimalDualHybridGradientParams.java.
boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasInfiniteConstraintBoundThreshold | ( | ) |
Constraint bounds with absolute value at least this threshold are replaced with infinities. NOTE: This primarily affects the relative convergence criteria. A smaller value makes the relative convergence criteria stronger. It also affects the problem statistics LOG()ed at the start of the run, and the default initial primal weight, since that is based on the norm of the bounds.
optional double infinite_constraint_bound_threshold = 22 [default = inf];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 2011 of file PrimalDualHybridGradientParams.java.
boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasInitialPrimalWeight | ( | ) |
The initial value of the primal weight (i.e., the ratio of primal and dual step sizes). The primal weight remains fixed throughout the solve if primal_weight_update_smoothing = 0.0. If unset, the default is the ratio of the norm of the objective vector to the L2 norm of the combined constraint bounds vector (as defined above). If this ratio is not finite and positive, then the default is 1.0 instead. For tuning, try powers of 10, for example, from 10^{-6} to 10^6.
optional double initial_primal_weight = 8;
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1657 of file PrimalDualHybridGradientParams.java.
boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasInitialStepSizeScaling | ( | ) |
Scaling factor applied to the initial step size (all step sizes if linesearch_rule == CONSTANT_STEP_SIZE_RULE).
optional double initial_step_size_scaling = 25 [default = 1];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1921 of file PrimalDualHybridGradientParams.java.
boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasL2NormRescaling | ( | ) |
If true, applies L_2 norm rescaling after the Ruiz rescaling. Heuristically this has been found to help convergence.
optional bool l2_norm_rescaling = 10 [default = true];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1748 of file PrimalDualHybridGradientParams.java.
boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasLinesearchRule | ( | ) |
Linesearch rule applied at each major iteration.
optional .operations_research.pdlp.PrimalDualHybridGradientParams.LinesearchRule linesearch_rule = 12 [default = ADAPTIVE_LINESEARCH_RULE];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1841 of file PrimalDualHybridGradientParams.java.
boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasLInfRuizIterations | ( | ) |
Number of L_infinity Ruiz rescaling iterations to apply to the constraint matrix. Zero disables this rescaling pass. Recommended values to try when tuning are 0, 5, and 10.
optional int32 l_inf_ruiz_iterations = 9 [default = 5];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1718 of file PrimalDualHybridGradientParams.java.
boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasLogIntervalSeconds | ( | ) |
Time between iteration-level statistics logging (if `verbosity_level > 1`). Since iteration-level statistics are only generated when performing termination checks, logs will be generated from next termination check after `log_interval_seconds` have elapsed. Should be >= 0.0. 0.0 (the default) means log statistics at every termination check.
optional double log_interval_seconds = 31 [default = 0];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1481 of file PrimalDualHybridGradientParams.java.
boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasMajorIterationFrequency | ( | ) |
The frequency at which extra work is performed to make major algorithmic decisions, e.g., performing restarts and updating the primal weight. Major iterations also trigger a termination check. For best performance using the NO_RESTARTS or EVERY_MAJOR_ITERATION rule, one should perform a log-scale grid search over this parameter, for example, over powers of two. ADAPTIVE_HEURISTIC is mostly insensitive to this value.
optional int32 major_iteration_frequency = 4 [default = 64];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1517 of file PrimalDualHybridGradientParams.java.
boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasMalitskyPockParameters | ( | ) |
optional .operations_research.pdlp.MalitskyPockParams malitsky_pock_parameters = 19;
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1890 of file PrimalDualHybridGradientParams.java.
boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasNecessaryReductionForRestart | ( | ) |
For ADAPTIVE_HEURISTIC only: A relative reduction in the potential function by this amount triggers a restart if, additionally, the quality of the iterates appears to be getting worse. The value must be in the interval [sufficient_reduction_for_restart, 1). Smaller values make restarts less frequent, and larger values make them more frequent.
optional double necessary_reduction_for_restart = 17 [default = 0.9];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1811 of file PrimalDualHybridGradientParams.java.
boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasNumShards | ( | ) |
For more efficient parallel computation, the matrices and vectors are divided (virtually) into num_shards shards. Results are computed independently for each shard and then combined. As a consequence, the order of computation, and hence floating point roundoff, depends on the number of shards so reproducible results require using the same value for num_shards. However, for efficiency num_shards should a be at least num_threads, and preferably at least 4*num_threads to allow better load balancing. If num_shards is positive, the computation will use that many shards. Otherwise a default that depends on num_threads will be used.
optional int32 num_shards = 27 [default = 0];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1334 of file PrimalDualHybridGradientParams.java.
boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasNumThreads | ( | ) |
The number of threads to use. Must be positive. Try various values of num_threads, up to the number of physical cores. Performance may not be monotonically increasing with the number of threads because of memory bandwidth limitations.
optional int32 num_threads = 2 [default = 1];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1296 of file PrimalDualHybridGradientParams.java.
boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasPresolveOptions | ( | ) |
optional .operations_research.pdlp.PrimalDualHybridGradientParams.PresolveOptions presolve_options = 16;
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1686 of file PrimalDualHybridGradientParams.java.
boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasPrimalWeightUpdateSmoothing | ( | ) |
This parameter controls exponential smoothing of log(primal_weight) when a primal weight update occurs (i.e., when the ratio of primal and dual step sizes is adjusted). At 0.0, the primal weight will be frozen at its initial value and there will be no dynamic updates in the algorithm. At 1.0, there is no smoothing in the updates. The default of 0.5 generally performs well, but has been observed on occasion to trigger unstable swings in the primal weight. We recommend also trying 0.0 (disabling primal weight updates), in which case you must also tune initial_primal_weight.
optional double primal_weight_update_smoothing = 7 [default = 0.5];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1617 of file PrimalDualHybridGradientParams.java.
boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasRecordIterationStats | ( | ) |
If true, the iteration_stats field of the SolveLog output will be populated at every iteration. Note that we only compute solution statistics at termination checks. Setting this parameter to true may substantially increase the size of the output.
optional bool record_iteration_stats = 3;
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1400 of file PrimalDualHybridGradientParams.java.
boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasRestartStrategy | ( | ) |
NO_RESTARTS and EVERY_MAJOR_ITERATION occasionally outperform the default. If using a strategy other than ADAPTIVE_HEURISTIC, you must also tune major_iteration_frequency.
optional .operations_research.pdlp.PrimalDualHybridGradientParams.RestartStrategy restart_strategy = 6 [default = ADAPTIVE_HEURISTIC];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1581 of file PrimalDualHybridGradientParams.java.
boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasSchedulerType | ( | ) |
The type of scheduler used for CPU multi-threading. See the documentation of the corresponding enum for more details.
optional .operations_research.pdlp.SchedulerType scheduler_type = 32 [default = SCHEDULER_TYPE_GOOGLE_THREADPOOL];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1369 of file PrimalDualHybridGradientParams.java.
boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasSufficientReductionForRestart | ( | ) |
For ADAPTIVE_HEURISTIC and ADAPTIVE_DISTANCE_BASED only: A relative reduction in the potential function by this amount always triggers a restart. Must be between 0.0 and 1.0.
optional double sufficient_reduction_for_restart = 11 [default = 0.1];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1778 of file PrimalDualHybridGradientParams.java.
boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasTerminationCheckFrequency | ( | ) |
The frequency (based on a counter reset every major iteration) to check for termination (involves extra work) and log iteration stats. Termination checks do not affect algorithmic progress unless termination is triggered.
optional int32 termination_check_frequency = 5 [default = 64];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1551 of file PrimalDualHybridGradientParams.java.
boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasTerminationCriteria | ( | ) |
optional .operations_research.pdlp.TerminationCriteria termination_criteria = 1;
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1263 of file PrimalDualHybridGradientParams.java.
boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasUseDiagonalQpTrustRegionSolver | ( | ) |
When solving QPs with diagonal objective matrices, this option can be turned on to enable an experimental solver that avoids linearization of the quadratic term. The `diagonal_qp_solver_accuracy` parameter controls the solve accuracy. TODO(user): Turn this option on by default for quadratic programs after numerical evaluation.
optional bool use_diagonal_qp_trust_region_solver = 23 [default = false];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 2079 of file PrimalDualHybridGradientParams.java.
boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasUseFeasibilityPolishing | ( | ) |
If true, periodically runs feasibility polishing, which attempts to move from latest average iterate to one that is closer to feasibility (i.e., has smaller primal and dual residuals) while probably increasing the objective gap. This is useful primarily when the feasibility tolerances are fairly tight and the objective gap tolerance is somewhat looser. Note that this does not change the termination criteria, but rather can help achieve the termination criteria more quickly when the objective gap is not as important as feasibility. `use_feasibility_polishing` cannot be used with glop presolve, and requires `handle_some_primal_gradients_on_finite_bounds_as_residuals == false`. `use_feasibility_polishing` can only be used with linear programs. Feasibility polishing runs two separate phases, primal feasibility and dual feasibility. The primal feasibility phase runs PDHG on the primal feasibility problem (obtained by changing the objective vector to all zeros), using the average primal iterate and zero dual (which is optimal for the primal feasibility problem) as the initial solution. The dual feasibility phase runs PDHG on the dual feasibility problem (obtained by changing all finite variable and constraint bounds to zero), using the average dual iterate and zero primal (which is optimal for the dual feasibility problem) as the initial solution. The primal solution from the primal feasibility phase and dual solution from the dual feasibility phase are then combined (forming a solution of type `POINT_TYPE_FEASIBILITY_POLISHING_SOLUTION`) and checked against the termination criteria.
optional bool use_feasibility_polishing = 30 [default = false];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 2171 of file PrimalDualHybridGradientParams.java.
boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasVerbosityLevel | ( | ) |
The verbosity of logging. 0: No informational logging. (Errors are logged.) 1: Summary statistics only. No iteration-level details. 2: A table of iteration-level statistics is logged. (See ToShortString() in primal_dual_hybrid_gradient.cc). 3: A more detailed table of iteration-level statistics is logged. (See ToString() in primal_dual_hybrid_gradient.cc). 4: For iteration-level details, prints the statistics of both the average (prefixed with A) and the current iterate (prefixed with C). Also prints internal algorithmic state and details. Logging at levels 2-4 also includes messages from level 1.
optional int32 verbosity_level = 26 [default = 0];
Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.
Definition at line 1440 of file PrimalDualHybridGradientParams.java.
|
protected |
Definition at line 69 of file PrimalDualHybridGradientParams.java.
final boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.isInitialized | ( | ) |
Definition at line 2278 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 2900 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 2903 of file PrimalDualHybridGradientParams.java.
Builder com.google.ortools.pdlp.PrimalDualHybridGradientParams.newBuilderForType | ( | ) |
Definition at line 2899 of file PrimalDualHybridGradientParams.java.
|
protected |
Definition at line 2913 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 2871 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 2877 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 2848 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 2852 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 2837 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 2842 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 2884 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 2890 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 2858 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 2863 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 2826 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 2831 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 5953 of file PrimalDualHybridGradientParams.java.
Builder com.google.ortools.pdlp.PrimalDualHybridGradientParams.toBuilder | ( | ) |
Definition at line 2907 of file PrimalDualHybridGradientParams.java.
void com.google.ortools.pdlp.PrimalDualHybridGradientParams.writeTo | ( | com.google.protobuf.CodedOutputStream | output | ) | throws java.io.IOException |
Definition at line 2288 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 1857 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 2212 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 2245 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 2100 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 2032 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 1995 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 1640 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 1909 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 1736 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 1705 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 1831 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 1466 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 1501 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 1883 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 1796 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 1315 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 1282 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 1679 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 1599 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 1938 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 1386 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 1569 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 1358 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 1765 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 1538 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 1256 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 2063 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 2135 of file PrimalDualHybridGradientParams.java.
|
static |
Definition at line 1419 of file PrimalDualHybridGradientParams.java.