Inheritance diagram for com.google.ortools.glop.GlopParameters:

Classes
class	Builder

enum	CostScalingAlgorithm

enum	InitialBasisHeuristic

enum	PricingRule

enum	ScalingAlgorithm

enum	SolverBehavior

Public Member Functions
boolean	hasScalingMethod ()

com.google.ortools.glop.GlopParameters.ScalingAlgorithm	getScalingMethod ()

boolean	hasFeasibilityRule ()

com.google.ortools.glop.GlopParameters.PricingRule	getFeasibilityRule ()

boolean	hasOptimizationRule ()

com.google.ortools.glop.GlopParameters.PricingRule	getOptimizationRule ()

boolean	hasRefactorizationThreshold ()

double	getRefactorizationThreshold ()

boolean	hasRecomputeReducedCostsThreshold ()

double	getRecomputeReducedCostsThreshold ()

boolean	hasRecomputeEdgesNormThreshold ()

double	getRecomputeEdgesNormThreshold ()

boolean	hasPrimalFeasibilityTolerance ()

double	getPrimalFeasibilityTolerance ()

boolean	hasDualFeasibilityTolerance ()

double	getDualFeasibilityTolerance ()

boolean	hasRatioTestZeroThreshold ()

double	getRatioTestZeroThreshold ()

boolean	hasHarrisToleranceRatio ()

double	getHarrisToleranceRatio ()

boolean	hasSmallPivotThreshold ()

double	getSmallPivotThreshold ()

boolean	hasMinimumAcceptablePivot ()

double	getMinimumAcceptablePivot ()

boolean	hasDropTolerance ()

double	getDropTolerance ()

boolean	hasUseScaling ()

boolean	getUseScaling ()

boolean	hasCostScaling ()

com.google.ortools.glop.GlopParameters.CostScalingAlgorithm	getCostScaling ()

boolean	hasInitialBasis ()

com.google.ortools.glop.GlopParameters.InitialBasisHeuristic	getInitialBasis ()

boolean	hasUseTransposedMatrix ()

boolean	getUseTransposedMatrix ()

boolean	hasBasisRefactorizationPeriod ()

int	getBasisRefactorizationPeriod ()

boolean	hasDynamicallyAdjustRefactorizationPeriod ()

boolean	getDynamicallyAdjustRefactorizationPeriod ()

boolean	hasSolveDualProblem ()

com.google.ortools.glop.GlopParameters.SolverBehavior	getSolveDualProblem ()

boolean	hasDualizerThreshold ()

double	getDualizerThreshold ()

boolean	hasSolutionFeasibilityTolerance ()

double	getSolutionFeasibilityTolerance ()

boolean	hasProvideStrongOptimalGuarantee ()

boolean	getProvideStrongOptimalGuarantee ()

boolean	hasChangeStatusToImprecise ()

boolean	getChangeStatusToImprecise ()

boolean	hasMaxNumberOfReoptimizations ()

double	getMaxNumberOfReoptimizations ()

boolean	hasLuFactorizationPivotThreshold ()

double	getLuFactorizationPivotThreshold ()

boolean	hasMaxTimeInSeconds ()

double	getMaxTimeInSeconds ()

boolean	hasMaxDeterministicTime ()

double	getMaxDeterministicTime ()

boolean	hasMaxNumberOfIterations ()

long	getMaxNumberOfIterations ()

boolean	hasMarkowitzZlatevParameter ()

int	getMarkowitzZlatevParameter ()

boolean	hasMarkowitzSingularityThreshold ()

double	getMarkowitzSingularityThreshold ()

boolean	hasUseDualSimplex ()

boolean	getUseDualSimplex ()

boolean	hasAllowSimplexAlgorithmChange ()

boolean	getAllowSimplexAlgorithmChange ()

boolean	hasDevexWeightsResetPeriod ()

int	getDevexWeightsResetPeriod ()

boolean	hasUsePreprocessing ()

boolean	getUsePreprocessing ()

boolean	hasUseMiddleProductFormUpdate ()

boolean	getUseMiddleProductFormUpdate ()

boolean	hasInitializeDevexWithColumnNorms ()

boolean	getInitializeDevexWithColumnNorms ()

boolean	hasExploitSingletonColumnInInitialBasis ()

boolean	getExploitSingletonColumnInInitialBasis ()

boolean	hasDualSmallPivotThreshold ()

double	getDualSmallPivotThreshold ()

boolean	hasPreprocessorZeroTolerance ()

double	getPreprocessorZeroTolerance ()

boolean	hasObjectiveLowerLimit ()

double	getObjectiveLowerLimit ()

boolean	hasObjectiveUpperLimit ()

double	getObjectiveUpperLimit ()

boolean	hasDegenerateMinistepFactor ()

double	getDegenerateMinistepFactor ()

boolean	hasRandomSeed ()

int	getRandomSeed ()

boolean	hasNumOmpThreads ()

int	getNumOmpThreads ()

boolean	hasPerturbCostsInDualSimplex ()

boolean	getPerturbCostsInDualSimplex ()

boolean	hasUseDedicatedDualFeasibilityAlgorithm ()

boolean	getUseDedicatedDualFeasibilityAlgorithm ()

boolean	hasRelativeCostPerturbation ()

double	getRelativeCostPerturbation ()

boolean	hasRelativeMaxCostPerturbation ()

double	getRelativeMaxCostPerturbation ()

boolean	hasInitialConditionNumberThreshold ()

double	getInitialConditionNumberThreshold ()

boolean	hasLogSearchProgress ()

boolean	getLogSearchProgress ()

boolean	hasLogToStdout ()

boolean	getLogToStdout ()

boolean	hasCrossoverBoundSnappingDistance ()

double	getCrossoverBoundSnappingDistance ()

boolean	hasPushToVertex ()

boolean	getPushToVertex ()

boolean	hasUseImpliedFreePreprocessor ()

boolean	getUseImpliedFreePreprocessor ()

boolean	hasMaxValidMagnitude ()

double	getMaxValidMagnitude ()

boolean	hasDropMagnitude ()

double	getDropMagnitude ()

boolean	hasDualPricePrioritizeNorm ()

boolean	getDualPricePrioritizeNorm ()

final boolean	isInitialized ()

void	writeTo (com.google.protobuf.CodedOutputStream output) throws java.io.IOException

int	getSerializedSize ()

boolean	equals (final java.lang.Object obj)

int	hashCode ()

Builder	newBuilderForType ()

Builder	toBuilder ()

com.google.protobuf.Parser< GlopParameters >	getParserForType ()

com.google.ortools.glop.GlopParameters	getDefaultInstanceForType ()

Static Public Member Functions
static final com.google.protobuf.Descriptors.Descriptor	getDescriptor ()

static com.google.ortools.glop.GlopParameters	parseFrom (java.nio.ByteBuffer data) throws com.google.protobuf.InvalidProtocolBufferException

static com.google.ortools.glop.GlopParameters	parseFrom (java.nio.ByteBuffer data, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws com.google.protobuf.InvalidProtocolBufferException

static com.google.ortools.glop.GlopParameters	parseFrom (com.google.protobuf.ByteString data) throws com.google.protobuf.InvalidProtocolBufferException

static com.google.ortools.glop.GlopParameters	parseFrom (com.google.protobuf.ByteString data, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws com.google.protobuf.InvalidProtocolBufferException

static com.google.ortools.glop.GlopParameters	parseFrom (byte[] data) throws com.google.protobuf.InvalidProtocolBufferException

static com.google.ortools.glop.GlopParameters	parseFrom (byte[] data, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws com.google.protobuf.InvalidProtocolBufferException

static com.google.ortools.glop.GlopParameters	parseFrom (java.io.InputStream input) throws java.io.IOException

static com.google.ortools.glop.GlopParameters	parseFrom (java.io.InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws java.io.IOException

static com.google.ortools.glop.GlopParameters	parseDelimitedFrom (java.io.InputStream input) throws java.io.IOException

static com.google.ortools.glop.GlopParameters	parseDelimitedFrom (java.io.InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws java.io.IOException

static com.google.ortools.glop.GlopParameters	parseFrom (com.google.protobuf.CodedInputStream input) throws java.io.IOException

static com.google.ortools.glop.GlopParameters	parseFrom (com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws java.io.IOException

static Builder	newBuilder ()

static Builder	newBuilder (com.google.ortools.glop.GlopParameters prototype)

static com.google.ortools.glop.GlopParameters	getDefaultInstance ()

static com.google.protobuf.Parser< GlopParameters >	parser ()

Static Public Attributes
static final int	SCALING_METHOD_FIELD_NUMBER = 57

static final int	FEASIBILITY_RULE_FIELD_NUMBER = 1

static final int	OPTIMIZATION_RULE_FIELD_NUMBER = 2

static final int	REFACTORIZATION_THRESHOLD_FIELD_NUMBER = 6

static final int	RECOMPUTE_REDUCED_COSTS_THRESHOLD_FIELD_NUMBER = 8

static final int	RECOMPUTE_EDGES_NORM_THRESHOLD_FIELD_NUMBER = 9

static final int	PRIMAL_FEASIBILITY_TOLERANCE_FIELD_NUMBER = 10

static final int	DUAL_FEASIBILITY_TOLERANCE_FIELD_NUMBER = 11

static final int	RATIO_TEST_ZERO_THRESHOLD_FIELD_NUMBER = 12

static final int	HARRIS_TOLERANCE_RATIO_FIELD_NUMBER = 13

static final int	SMALL_PIVOT_THRESHOLD_FIELD_NUMBER = 14

static final int	MINIMUM_ACCEPTABLE_PIVOT_FIELD_NUMBER = 15

static final int	DROP_TOLERANCE_FIELD_NUMBER = 52

static final int	USE_SCALING_FIELD_NUMBER = 16

static final int	COST_SCALING_FIELD_NUMBER = 60

static final int	INITIAL_BASIS_FIELD_NUMBER = 17

static final int	USE_TRANSPOSED_MATRIX_FIELD_NUMBER = 18

static final int	BASIS_REFACTORIZATION_PERIOD_FIELD_NUMBER = 19

static final int	DYNAMICALLY_ADJUST_REFACTORIZATION_PERIOD_FIELD_NUMBER = 63

static final int	SOLVE_DUAL_PROBLEM_FIELD_NUMBER = 20

static final int	DUALIZER_THRESHOLD_FIELD_NUMBER = 21

static final int	SOLUTION_FEASIBILITY_TOLERANCE_FIELD_NUMBER = 22

static final int	PROVIDE_STRONG_OPTIMAL_GUARANTEE_FIELD_NUMBER = 24

static final int	CHANGE_STATUS_TO_IMPRECISE_FIELD_NUMBER = 58

static final int	MAX_NUMBER_OF_REOPTIMIZATIONS_FIELD_NUMBER = 56

static final int	LU_FACTORIZATION_PIVOT_THRESHOLD_FIELD_NUMBER = 25

static final int	MAX_TIME_IN_SECONDS_FIELD_NUMBER = 26

static final int	MAX_DETERMINISTIC_TIME_FIELD_NUMBER = 45

static final int	MAX_NUMBER_OF_ITERATIONS_FIELD_NUMBER = 27

static final int	MARKOWITZ_ZLATEV_PARAMETER_FIELD_NUMBER = 29

static final int	MARKOWITZ_SINGULARITY_THRESHOLD_FIELD_NUMBER = 30

static final int	USE_DUAL_SIMPLEX_FIELD_NUMBER = 31

static final int	ALLOW_SIMPLEX_ALGORITHM_CHANGE_FIELD_NUMBER = 32

static final int	DEVEX_WEIGHTS_RESET_PERIOD_FIELD_NUMBER = 33

static final int	USE_PREPROCESSING_FIELD_NUMBER = 34

static final int	USE_MIDDLE_PRODUCT_FORM_UPDATE_FIELD_NUMBER = 35

static final int	INITIALIZE_DEVEX_WITH_COLUMN_NORMS_FIELD_NUMBER = 36

static final int	EXPLOIT_SINGLETON_COLUMN_IN_INITIAL_BASIS_FIELD_NUMBER = 37

static final int	DUAL_SMALL_PIVOT_THRESHOLD_FIELD_NUMBER = 38

static final int	PREPROCESSOR_ZERO_TOLERANCE_FIELD_NUMBER = 39

static final int	OBJECTIVE_LOWER_LIMIT_FIELD_NUMBER = 40

static final int	OBJECTIVE_UPPER_LIMIT_FIELD_NUMBER = 41

static final int	DEGENERATE_MINISTEP_FACTOR_FIELD_NUMBER = 42

static final int	RANDOM_SEED_FIELD_NUMBER = 43

static final int	NUM_OMP_THREADS_FIELD_NUMBER = 44

static final int	PERTURB_COSTS_IN_DUAL_SIMPLEX_FIELD_NUMBER = 53

static final int	USE_DEDICATED_DUAL_FEASIBILITY_ALGORITHM_FIELD_NUMBER = 62

static final int	RELATIVE_COST_PERTURBATION_FIELD_NUMBER = 54

static final int	RELATIVE_MAX_COST_PERTURBATION_FIELD_NUMBER = 55

static final int	INITIAL_CONDITION_NUMBER_THRESHOLD_FIELD_NUMBER = 59

static final int	LOG_SEARCH_PROGRESS_FIELD_NUMBER = 61

static final int	LOG_TO_STDOUT_FIELD_NUMBER = 66

static final int	CROSSOVER_BOUND_SNAPPING_DISTANCE_FIELD_NUMBER = 64

static final int	PUSH_TO_VERTEX_FIELD_NUMBER = 65

static final int	USE_IMPLIED_FREE_PREPROCESSOR_FIELD_NUMBER = 67

static final int	MAX_VALID_MAGNITUDE_FIELD_NUMBER = 70

static final int	DROP_MAGNITUDE_FIELD_NUMBER = 71

static final int	DUAL_PRICE_PRIORITIZE_NORM_FIELD_NUMBER = 69

Protected Member Functions
com.google.protobuf.GeneratedMessage.FieldAccessorTable	internalGetFieldAccessorTable ()

Builder	newBuilderForType (com.google.protobuf.GeneratedMessage.BuilderParent parent)

Detailed Description

next id = 72

Protobuf type operations_research.glop.GlopParameters

Definition at line 15 of file GlopParameters.java.

Member Function Documentation

◆ equals()

boolean com.google.ortools.glop.GlopParameters.equals ( final java.lang.Object obj )

Definition at line 3227 of file GlopParameters.java.

◆ getAllowSimplexAlgorithmChange()

boolean com.google.ortools.glop.GlopParameters.getAllowSimplexAlgorithmChange ( )

During incremental solve, let the solver decide if it use the primal or
dual simplex algorithm depending on the current solution and on the new
problem. Note that even if this is true, the value of use_dual_simplex
still indicates the default algorithm that the solver will use.

optional bool allow_simplex_algorithm_change = 32 [default = false];

Returns: The allowSimplexAlgorithmChange.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1929 of file GlopParameters.java.

◆ getBasisRefactorizationPeriod()

int com.google.ortools.glop.GlopParameters.getBasisRefactorizationPeriod ( )

Number of iterations between two basis refactorizations. Note that various
conditions in the algorithm may trigger a refactorization before this
period is reached. Set this to 0 if you want to refactorize at each step.

optional int32 basis_refactorization_period = 19 [default = 64];

Returns: The basisRefactorizationPeriod.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1423 of file GlopParameters.java.

◆ getChangeStatusToImprecise()

boolean com.google.ortools.glop.GlopParameters.getChangeStatusToImprecise ( )

If true, the internal API will change the return status to imprecise if the
solution does not respect the internal tolerances.

optional bool change_status_to_imprecise = 58 [default = true];

Returns: The changeStatusToImprecise.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1650 of file GlopParameters.java.

◆ getCostScaling()

com.google.ortools.glop.GlopParameters.CostScalingAlgorithm com.google.ortools.glop.GlopParameters.getCostScaling ( )

optional .operations_research.glop.GlopParameters.CostScalingAlgorithm cost_scaling = 60 [default = CONTAIN_ONE_COST_SCALING];

Returns: The costScaling.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1332 of file GlopParameters.java.

◆ getCrossoverBoundSnappingDistance()

double com.google.ortools.glop.GlopParameters.getCrossoverBoundSnappingDistance ( )

If the starting basis contains FREE variable with bounds, we will move
any such variable to their closer bounds if the distance is smaller than
this parameter.

The starting statuses can contains FREE variables with bounds, if a user
set it like this externally. Also, any variable with an initial BASIC
status that was not kept in the initial basis is marked as FREE before this
step is applied.

Note that by default a FREE variable is assumed to be zero unless a
starting value was specified via SetStartingVariableValuesForNextSolve().

Note that, at the end of the solve, some of these FREE variable with bounds
and an interior point value might still be left in the final solution.
Enable push_to_vertex to clean these up.

optional double crossover_bound_snapping_distance = 64 [default = inf];

Returns: The crossoverBoundSnappingDistance.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2625 of file GlopParameters.java.

◆ getDefaultInstance()

static com.google.ortools.glop.GlopParameters com.google.ortools.glop.GlopParameters.getDefaultInstance ( )

static

Definition at line 8899 of file GlopParameters.java.

◆ getDefaultInstanceForType()

com.google.ortools.glop.GlopParameters com.google.ortools.glop.GlopParameters.getDefaultInstanceForType ( )

Definition at line 8935 of file GlopParameters.java.

◆ getDegenerateMinistepFactor()

double com.google.ortools.glop.GlopParameters.getDegenerateMinistepFactor ( )

During a degenerate iteration, the more conservative approach is to do a
step of length zero (while shifting the bound of the leaving variable).
That is, the variable values are unchanged for the primal simplex or the
reduced cost are unchanged for the dual simplex. However, instead of doing
a step of length zero, it seems to be better on degenerate problems to do a
small positive step. This is what is recommended in the EXPAND procedure
described in:
P. E. Gill, W. Murray, M. A. Saunders, and M. H. Wright. "A practical anti-
cycling procedure for linearly constrained optimization".
Mathematical Programming, 45:437&#92;u2013474, 1989.

Here, during a degenerate iteration we do a small positive step of this
factor times the primal (resp. dual) tolerance. In the primal simplex, this
may effectively push variable values (very slightly) further out of their
bounds (resp. reduced costs for the dual simplex).

Setting this to zero reverts to the more conservative approach of a zero
step during degenerate iterations.

optional double degenerate_ministep_factor = 42 [default = 0.01];

Returns: The degenerateMinistepFactor.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2271 of file GlopParameters.java.

◆ getDescriptor()

static final com.google.protobuf.Descriptors.Descriptor com.google.ortools.glop.GlopParameters.getDescriptor ( )

static

Definition at line 90 of file GlopParameters.java.

◆ getDevexWeightsResetPeriod()

int com.google.ortools.glop.GlopParameters.getDevexWeightsResetPeriod ( )

Devex weights will be reset to 1.0 after that number of updates.

optional int32 devex_weights_reset_period = 33 [default = 150];

Returns: The devexWeightsResetPeriod.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1956 of file GlopParameters.java.

◆ getDropMagnitude()

double com.google.ortools.glop.GlopParameters.getDropMagnitude ( )

Value in the input LP lower than this will be ignored. This is similar to
drop_tolerance but more aggressive as this is used before scaling. This is
mainly here to avoid underflow and have simpler invariant in the code, like
a * b == 0 iff a or b is zero and things like this.

optional double drop_magnitude = 71 [default = 1e-30];

Returns: The dropMagnitude.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2759 of file GlopParameters.java.

◆ getDropTolerance()

double com.google.ortools.glop.GlopParameters.getDropTolerance ( )

In order to increase the sparsity of the manipulated vectors, floating
point values with a magnitude smaller than this parameter are set to zero
(only in some places). This parameter should be positive or zero.

optional double drop_tolerance = 52 [default = 1e-14];

Returns: The dropTolerance.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1286 of file GlopParameters.java.

◆ getDualFeasibilityTolerance()

double com.google.ortools.glop.GlopParameters.getDualFeasibilityTolerance ( )

Variables whose reduced costs have an absolute value smaller than this
tolerance are not considered as entering candidates. That is they do not
take part in deciding whether a solution is dual-feasible or not.

Note that this value can temporarily increase during the execution of the
algorithm if the estimated precision of the reduced costs is higher than
this tolerance. Note also that we scale the costs (in the presolve step) so
that the cost magnitude range contains one.

This is also known as the optimality tolerance in other solvers.

optional double dual_feasibility_tolerance = 11 [default = 1e-08];

Returns: The dualFeasibilityTolerance.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1109 of file GlopParameters.java.

◆ getDualizerThreshold()

double com.google.ortools.glop.GlopParameters.getDualizerThreshold ( )

When solve_dual_problem is LET_SOLVER_DECIDE, take the dual if the number
of constraints of the problem is more than this threshold times the number
of variables.

optional double dualizer_threshold = 21 [default = 1.5];

Returns: The dualizerThreshold.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1519 of file GlopParameters.java.

◆ getDualPricePrioritizeNorm()

boolean com.google.ortools.glop.GlopParameters.getDualPricePrioritizeNorm ( )

On some problem like stp3d or pds-100 this makes a huge difference in
speed and number of iterations of the dual simplex.

optional bool dual_price_prioritize_norm = 69 [default = false];

Returns: The dualPricePrioritizeNorm.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2788 of file GlopParameters.java.

◆ getDualSmallPivotThreshold()

double com.google.ortools.glop.GlopParameters.getDualSmallPivotThreshold ( )

Like small_pivot_threshold but for the dual simplex. This is needed because
the dual algorithm does not interpret this value in the same way.
TODO(user): Clean this up and use the same small pivot detection.

optional double dual_small_pivot_threshold = 38 [default = 0.0001];

Returns: The dualSmallPivotThreshold.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2111 of file GlopParameters.java.

◆ getDynamicallyAdjustRefactorizationPeriod()

boolean com.google.ortools.glop.GlopParameters.getDynamicallyAdjustRefactorizationPeriod ( )

If this is true, then basis_refactorization_period becomes a lower bound on
the number of iterations between two refactorization (provided there is no
numerical accuracy issues). Depending on the estimated time to refactorize
vs the extra time spend in each solves because of the LU update, we try to
balance the two times.

optional bool dynamically_adjust_refactorization_period = 63 [default = true];

Returns: The dynamicallyAdjustRefactorizationPeriod.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1458 of file GlopParameters.java.

◆ getExploitSingletonColumnInInitialBasis()

boolean com.google.ortools.glop.GlopParameters.getExploitSingletonColumnInInitialBasis ( )

Whether or not we exploit the singleton columns already present in the
problem when we create the initial basis.

optional bool exploit_singleton_column_in_initial_basis = 37 [default = true];

Returns: The exploitSingletonColumnInInitialBasis.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2080 of file GlopParameters.java.

◆ getFeasibilityRule()

com.google.ortools.glop.GlopParameters.PricingRule com.google.ortools.glop.GlopParameters.getFeasibilityRule ( )

PricingRule to use during the feasibility phase.

optional .operations_research.glop.GlopParameters.PricingRule feasibility_rule = 1 [default = STEEPEST_EDGE];

Returns: The feasibilityRule.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 891 of file GlopParameters.java.

◆ getHarrisToleranceRatio()

double com.google.ortools.glop.GlopParameters.getHarrisToleranceRatio ( )

This impacts the ratio test and indicates by how much we allow a basic
variable value that we move to go out of bounds. The value should be in
[0.0, 1.0) and should be interpreted as a ratio of the
primal_feasibility_tolerance. Setting this to 0.0 basically disables the
Harris ratio test while setting this too close to 1.0 will make it
difficult to keep the variable values inside their bounds modulo the
primal_feasibility_tolerance.

Note that the same comment applies to the dual simplex ratio test. There,
we allow the reduced costs to be of an infeasible sign by as much as this
ratio times the dual_feasibility_tolerance.

optional double harris_tolerance_ratio = 13 [default = 0.5];

Returns: The harrisToleranceRatio.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1195 of file GlopParameters.java.

◆ getInitialBasis()

com.google.ortools.glop.GlopParameters.InitialBasisHeuristic com.google.ortools.glop.GlopParameters.getInitialBasis ( )

What heuristic is used to try to replace the fixed slack columns in the
initial basis of the primal simplex.

optional .operations_research.glop.GlopParameters.InitialBasisHeuristic initial_basis = 17 [default = TRIANGULAR];

Returns: The initialBasis.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1360 of file GlopParameters.java.

◆ getInitialConditionNumberThreshold()

double com.google.ortools.glop.GlopParameters.getInitialConditionNumberThreshold ( )

If our upper bound on the condition number of the initial basis (from our
heurisitic or a warm start) is above this threshold, we revert to an all
slack basis.

optional double initial_condition_number_threshold = 59 [default = 1e+50];

Returns: The initialConditionNumberThreshold.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2512 of file GlopParameters.java.

◆ getInitializeDevexWithColumnNorms()

boolean com.google.ortools.glop.GlopParameters.getInitializeDevexWithColumnNorms ( )

Whether we initialize devex weights to 1.0 or to the norms of the matrix
columns.

optional bool initialize_devex_with_column_norms = 36 [default = true];

Returns: The initializeDevexWithColumnNorms.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2051 of file GlopParameters.java.

◆ getLogSearchProgress()

boolean com.google.ortools.glop.GlopParameters.getLogSearchProgress ( )

If true, logs the progress of a solve to LOG(INFO). Note that the same
messages can also be turned on by displaying logs at level 1 for the
relevant files.

optional bool log_search_progress = 61 [default = false];

Returns: The logSearchProgress.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2543 of file GlopParameters.java.

◆ getLogToStdout()

boolean com.google.ortools.glop.GlopParameters.getLogToStdout ( )

If true, logs will be displayed to stdout instead of using Google log info.

optional bool log_to_stdout = 66 [default = true];

Returns: The logToStdout.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2570 of file GlopParameters.java.

◆ getLuFactorizationPivotThreshold()

double com.google.ortools.glop.GlopParameters.getLuFactorizationPivotThreshold ( )

Threshold for LU-factorization: for stability reasons, the magnitude of the
chosen pivot at a given step is guaranteed to be greater than this
threshold times the maximum magnitude of all the possible pivot choices in
the same column. The value must be in [0,1].

optional double lu_factorization_pivot_threshold = 25 [default = 0.01];

Returns: The luFactorizationPivotThreshold.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1716 of file GlopParameters.java.

◆ getMarkowitzSingularityThreshold()

double com.google.ortools.glop.GlopParameters.getMarkowitzSingularityThreshold ( )

If a pivot magnitude is smaller than this during the Markowitz LU
factorization, then the matrix is assumed to be singular. Note that
this is an absolute threshold and is not relative to the other possible
pivots on the same column (see lu_factorization_pivot_threshold).

optional double markowitz_singularity_threshold = 30 [default = 1e-15];

Returns: The markowitzSingularityThreshold.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1869 of file GlopParameters.java.

◆ getMarkowitzZlatevParameter()

int com.google.ortools.glop.GlopParameters.getMarkowitzZlatevParameter ( )

How many columns do we look at in the Markowitz pivoting rule to find
a good pivot. See markowitz.h.

optional int32 markowitz_zlatev_parameter = 29 [default = 3];

Returns: The markowitzZlatevParameter.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1836 of file GlopParameters.java.

◆ getMaxDeterministicTime()

double com.google.ortools.glop.GlopParameters.getMaxDeterministicTime ( )

Maximum deterministic time allowed to solve a problem. The deterministic
time is more or less correlated to the running time, and its unit should
be around the second (at least on a Xeon(R) CPU E5-1650 v2 &#64; 3.50GHz).

TODO(user): Improve the correlation.

optional double max_deterministic_time = 45 [default = inf];

Returns: The maxDeterministicTime.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1778 of file GlopParameters.java.

◆ getMaxNumberOfIterations()

long com.google.ortools.glop.GlopParameters.getMaxNumberOfIterations ( )

Maximum number of simplex iterations to solve a problem.
A value of -1 means no limit.

optional int64 max_number_of_iterations = 27 [default = -1];

Returns: The maxNumberOfIterations.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1807 of file GlopParameters.java.

◆ getMaxNumberOfReoptimizations()

double com.google.ortools.glop.GlopParameters.getMaxNumberOfReoptimizations ( )

When the solution of phase II is imprecise, we re-run the phase II with the
opposite algorithm from that imprecise solution (i.e., if primal or dual
simplex was used, we use dual or primal simplex, respectively). We repeat
such re-optimization until the solution is precise, or we hit this limit.

optional double max_number_of_reoptimizations = 56 [default = 40];

Returns: The maxNumberOfReoptimizations.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1683 of file GlopParameters.java.

◆ getMaxTimeInSeconds()

double com.google.ortools.glop.GlopParameters.getMaxTimeInSeconds ( )

Maximum time allowed in seconds to solve a problem.

optional double max_time_in_seconds = 26 [default = inf];

Returns: The maxTimeInSeconds.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1743 of file GlopParameters.java.

◆ getMaxValidMagnitude()

double com.google.ortools.glop.GlopParameters.getMaxValidMagnitude ( )

Any finite values in the input LP 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. In practice, users
shouldn't use super large values in an LP. With the default threshold, even
evaluating large constraint with variables at their bound shouldn't cause
any overflow.

optional double max_valid_magnitude = 70 [default = 1e+30];

Returns: The maxValidMagnitude.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2726 of file GlopParameters.java.

◆ getMinimumAcceptablePivot()

double com.google.ortools.glop.GlopParameters.getMinimumAcceptablePivot ( )

We never follow a basis change with a pivot under this threshold.

optional double minimum_acceptable_pivot = 15 [default = 1e-06];

Returns: The minimumAcceptablePivot.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1255 of file GlopParameters.java.

◆ getNumOmpThreads()

int com.google.ortools.glop.GlopParameters.getNumOmpThreads ( )

Number of threads in the OMP parallel sections. If left to 1, the code will
not create any OMP threads and will remain single-threaded.

optional int32 num_omp_threads = 44 [default = 1];

Returns: The numOmpThreads.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2355 of file GlopParameters.java.

◆ getObjectiveLowerLimit()

double com.google.ortools.glop.GlopParameters.getObjectiveLowerLimit ( )

The solver will stop as soon as it has proven that the objective is smaller
than objective_lower_limit or greater than objective_upper_limit. Depending
on the simplex algorithm (primal or dual) and the optimization direction,
note that only one bound will be used at the time.

Important: The solver does not add any tolerances to these values, and as
soon as the objective (as computed by the solver, so with some imprecision)
crosses one of these bounds (strictly), the search will stop. It is up to
the client to add any tolerance if needed.

optional double objective_lower_limit = 40 [default = -inf];

Returns: The objectiveLowerLimit.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2191 of file GlopParameters.java.

◆ getObjectiveUpperLimit()

double com.google.ortools.glop.GlopParameters.getObjectiveUpperLimit ( )

optional double objective_upper_limit = 41 [default = inf];

Returns: The objectiveUpperLimit.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2210 of file GlopParameters.java.

◆ getOptimizationRule()

com.google.ortools.glop.GlopParameters.PricingRule com.google.ortools.glop.GlopParameters.getOptimizationRule ( )

PricingRule to use during the optimization phase.

optional .operations_research.glop.GlopParameters.PricingRule optimization_rule = 2 [default = STEEPEST_EDGE];

Returns: The optimizationRule.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 917 of file GlopParameters.java.

◆ getParserForType()

com.google.protobuf.Parser< GlopParameters > com.google.ortools.glop.GlopParameters.getParserForType ( )

Definition at line 8930 of file GlopParameters.java.

◆ getPerturbCostsInDualSimplex()

boolean com.google.ortools.glop.GlopParameters.getPerturbCostsInDualSimplex ( )

When this is true, then the costs are randomly perturbed before the dual
simplex is even started. This has been shown to improve the dual simplex
performance. For a good reference, see Huangfu Q (2013) "High performance
simplex solver", Ph.D, dissertation, University of Edinburgh.

optional bool perturb_costs_in_dual_simplex = 53 [default = false];

Returns: The perturbCostsInDualSimplex.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2388 of file GlopParameters.java.

◆ getPreprocessorZeroTolerance()

double com.google.ortools.glop.GlopParameters.getPreprocessorZeroTolerance ( )

A floating point tolerance used by the preprocessors. This is used for
things like detecting if two columns/rows are proportional or if an
interval is empty.

Note that the preprocessors also use solution_feasibility_tolerance() to
detect if a problem is infeasible.

optional double preprocessor_zero_tolerance = 39 [default = 1e-09];

Returns: The preprocessorZeroTolerance.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2148 of file GlopParameters.java.

◆ getPrimalFeasibilityTolerance()

double com.google.ortools.glop.GlopParameters.getPrimalFeasibilityTolerance ( )

This tolerance indicates by how much we allow the variable values to go out
of bounds and still consider the current solution primal-feasible. We also
use the same tolerance for the error A.x - b. Note that the two errors are
closely related if A is scaled in such a way that the greatest coefficient
magnitude on each column is 1.0.

This is also simply called feasibility tolerance in other solvers.

optional double primal_feasibility_tolerance = 10 [default = 1e-08];

Returns: The primalFeasibilityTolerance.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1064 of file GlopParameters.java.

◆ getProvideStrongOptimalGuarantee()

boolean com.google.ortools.glop.GlopParameters.getProvideStrongOptimalGuarantee ( )

If true, then when the solver returns a solution with an OPTIMAL status,
we can guarantee that:
- The primal variable are in their bounds.
- The dual variable are in their bounds.
- If we modify each component of the right-hand side a bit and each
component of the objective function a bit, then the pair (primal values,
dual values) is an EXACT optimal solution of the perturbed problem.
- The modifications above are smaller than the associated tolerances as
defined in the comment for solution_feasibility_tolerance (*).

(*): This is the only place where the guarantee is not tight since we
compute the upper bounds with scalar product of the primal/dual
solution and the initial problem coefficients with only double precision.

Note that whether or not this option is true, we still check the
primal/dual infeasibility and objective gap. However if it is false, we
don't move the primal/dual values within their bounds and leave them
untouched.

optional bool provide_strong_optimal_guarantee = 24 [default = true];

Returns: The provideStrongOptimalGuarantee.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1621 of file GlopParameters.java.

◆ getPushToVertex()

boolean com.google.ortools.glop.GlopParameters.getPushToVertex ( )

If the optimization phases finishes with super-basic variables (i.e.,
variables that either 1) have bounds but are FREE in the basis, or 2) have
no bounds and are FREE in the basis at a nonzero value), then run a "push"
phase to push these variables to bounds, obtaining a vertex solution. Note
this situation can happen only if a starting value was specified via
SetStartingVariableValuesForNextSolve().

optional bool push_to_vertex = 65 [default = true];

Returns: The pushToVertex.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2662 of file GlopParameters.java.

◆ getRandomSeed()

int com.google.ortools.glop.GlopParameters.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.
Note that this may lead to a different solution, for example a different
optimal basis.

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.

Also note that the solver is fully deterministic: two runs of the same
binary, on the same machine, on the exact same data and with the same
parameters will go through the exact same iterations. If they hit a time
limit, they might of course yield different results because one will have
advanced farther than the other.

optional int32 random_seed = 43 [default = 1];

Returns: The randomSeed.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2326 of file GlopParameters.java.

◆ getRatioTestZeroThreshold()

double com.google.ortools.glop.GlopParameters.getRatioTestZeroThreshold ( )

During the primal simplex (resp. dual simplex), the coefficients of the
direction (resp. update row) with a magnitude lower than this threshold are
not considered during the ratio test. This tolerance is related to the
precision at which a Solve() involving the basis matrix can be performed.

TODO(user): Automatically increase it when we detect that the precision
of the Solve() is worse than this.

optional double ratio_test_zero_threshold = 12 [default = 1e-09];

Returns: The ratioTestZeroThreshold.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1148 of file GlopParameters.java.

◆ getRecomputeEdgesNormThreshold()

double com.google.ortools.glop.GlopParameters.getRecomputeEdgesNormThreshold ( )

Note that the threshold is a relative error on the actual norm (not the
squared one) and that edge norms are always greater than 1. Recomputing
norms is a really expensive operation and a large threshold is ok since
this doesn't impact directly the solution but just the entering variable
choice.

optional double recompute_edges_norm_threshold = 9 [default = 100];

Returns: The recomputeEdgesNormThreshold.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1025 of file GlopParameters.java.

◆ getRecomputeReducedCostsThreshold()

double com.google.ortools.glop.GlopParameters.getRecomputeReducedCostsThreshold ( )

We estimate the accuracy of the iteratively computed reduced costs. If
it falls below this threshold, we reinitialize them from scratch. Note
that such an operation is pretty fast, so we can use a low threshold.
It is important to have a good accuracy here (better than the
dual_feasibility_tolerance below) to be sure of the sign of such a cost.

optional double recompute_reduced_costs_threshold = 8 [default = 1e-08];

Returns: The recomputeReducedCostsThreshold.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 990 of file GlopParameters.java.

◆ getRefactorizationThreshold()

double com.google.ortools.glop.GlopParameters.getRefactorizationThreshold ( )

We estimate the factorization accuracy of B during each pivot by using
the fact that we can compute the pivot coefficient in two ways:
- From direction[leaving_row].
- From update_row[entering_column].
If the two values have a relative difference above this threshold, we
trigger a refactorization.

optional double refactorization_threshold = 6 [default = 1e-09];

Returns: The refactorizationThreshold.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 955 of file GlopParameters.java.

◆ getRelativeCostPerturbation()

double com.google.ortools.glop.GlopParameters.getRelativeCostPerturbation ( )

The magnitude of the cost perturbation is given by
RandomIn(1.0, 2.0) * (
relative_cost_perturbation * cost
+ relative_max_cost_perturbation * max_cost);

optional double relative_cost_perturbation = 54 [default = 1e-05];

Returns: The relativeCostPerturbation.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2462 of file GlopParameters.java.

◆ getRelativeMaxCostPerturbation()

double com.google.ortools.glop.GlopParameters.getRelativeMaxCostPerturbation ( )

optional double relative_max_cost_perturbation = 55 [default = 1e-07];

Returns: The relativeMaxCostPerturbation.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2481 of file GlopParameters.java.

◆ getScalingMethod()

com.google.ortools.glop.GlopParameters.ScalingAlgorithm com.google.ortools.glop.GlopParameters.getScalingMethod ( )

optional .operations_research.glop.GlopParameters.ScalingAlgorithm scaling_method = 57 [default = EQUILIBRATION];

Returns: The scalingMethod.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 865 of file GlopParameters.java.

◆ getSerializedSize()

int com.google.ortools.glop.GlopParameters.getSerializedSize ( )

Definition at line 2984 of file GlopParameters.java.

◆ getSmallPivotThreshold()

double com.google.ortools.glop.GlopParameters.getSmallPivotThreshold ( )

When we choose the leaving variable, we want to avoid small pivot because
they are the less precise and may cause numerical instabilities. For a
pivot under this threshold times the infinity norm of the direction, we try
various countermeasures in order to avoid using it.

optional double small_pivot_threshold = 14 [default = 1e-06];

Returns: The smallPivotThreshold.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1228 of file GlopParameters.java.

◆ getSolutionFeasibilityTolerance()

double com.google.ortools.glop.GlopParameters.getSolutionFeasibilityTolerance ( )

When the problem status is OPTIMAL, we check the optimality using this
relative tolerance and change the status to IMPRECISE if an issue is
detected.

The tolerance is "relative" in the sense that our thresholds are:
- tolerance * max(1.0, abs(bound)) for crossing a given bound.
- tolerance * max(1.0, abs(cost)) for an infeasible reduced cost.
- tolerance for an infeasible dual value.

optional double solution_feasibility_tolerance = 22 [default = 1e-06];

Returns: The solutionFeasibilityTolerance.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1560 of file GlopParameters.java.

◆ getSolveDualProblem()

com.google.ortools.glop.GlopParameters.SolverBehavior com.google.ortools.glop.GlopParameters.getSolveDualProblem ( )

Whether or not we solve the dual of the given problem.
With a value of auto, the algorithm decide which approach is probably the
fastest depending on the problem dimensions (see dualizer_threshold).

optional .operations_research.glop.GlopParameters.SolverBehavior solve_dual_problem = 20 [default = LET_SOLVER_DECIDE];

Returns: The solveDualProblem.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1487 of file GlopParameters.java.

◆ getUseDedicatedDualFeasibilityAlgorithm()

boolean com.google.ortools.glop.GlopParameters.getUseDedicatedDualFeasibilityAlgorithm ( )

We have two possible dual phase I algorithms. Both work on an LP that
minimize the sum of dual infeasiblities. One use dedicated code (when this
param is true), the other one use exactly the same code as the dual phase
II but on an auxiliary problem where the variable bounds of the original
problem are changed.

TODO(user): For now we have both, but ideally the non-dedicated version
will win since it is a lot less code to maintain.

optional bool use_dedicated_dual_feasibility_algorithm = 62 [default = true];

Returns: The useDedicatedDualFeasibilityAlgorithm.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2429 of file GlopParameters.java.

◆ getUseDualSimplex()

boolean com.google.ortools.glop.GlopParameters.getUseDualSimplex ( )

Whether or not we use the dual simplex algorithm instead of the primal.

optional bool use_dual_simplex = 31 [default = false];

Returns: The useDualSimplex.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1896 of file GlopParameters.java.

◆ getUseImpliedFreePreprocessor()

boolean com.google.ortools.glop.GlopParameters.getUseImpliedFreePreprocessor ( )

If presolve runs, include the pass that detects implied free variables.

optional bool use_implied_free_preprocessor = 67 [default = true];

Returns: The useImpliedFreePreprocessor.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2689 of file GlopParameters.java.

◆ getUseMiddleProductFormUpdate()

boolean com.google.ortools.glop.GlopParameters.getUseMiddleProductFormUpdate ( )

Whether or not to use the middle product form update rather than the
standard eta LU update. The middle form product update should be a lot more
efficient (close to the Forrest-Tomlin update, a bit slower but easier to
implement). See for more details:
Qi Huangfu, J. A. Julian Hall, "Novel update techniques for the revised
simplex method", 28 january 2013, Technical Report ERGO-13-0001
http://www.maths.ed.ac.uk/hall/HuHa12/ERGO-13-001.pdf

optional bool use_middle_product_form_update = 35 [default = true];

Returns: The useMiddleProductFormUpdate.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2022 of file GlopParameters.java.

◆ getUsePreprocessing()

boolean com.google.ortools.glop.GlopParameters.getUsePreprocessing ( )

Whether or not we use advanced preprocessing techniques.

optional bool use_preprocessing = 34 [default = true];

Returns: The usePreprocessing.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1983 of file GlopParameters.java.

◆ getUseScaling()

boolean com.google.ortools.glop.GlopParameters.getUseScaling ( )

Whether or not we scale the matrix A so that the maximum coefficient on
each line and each column is 1.0.

optional bool use_scaling = 16 [default = true];

Returns: The useScaling.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1315 of file GlopParameters.java.

◆ getUseTransposedMatrix()

boolean com.google.ortools.glop.GlopParameters.getUseTransposedMatrix ( )

Whether or not we keep a transposed version of the matrix A to speed-up the
pricing at the cost of extra memory and the initial tranposition
computation.

optional bool use_transposed_matrix = 18 [default = true];

Returns: The useTransposedMatrix.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1392 of file GlopParameters.java.

◆ hasAllowSimplexAlgorithmChange()

boolean com.google.ortools.glop.GlopParameters.hasAllowSimplexAlgorithmChange ( )

During incremental solve, let the solver decide if it use the primal or
dual simplex algorithm depending on the current solution and on the new
problem. Note that even if this is true, the value of use_dual_simplex
still indicates the default algorithm that the solver will use.

optional bool allow_simplex_algorithm_change = 32 [default = false];

Returns: Whether the allowSimplexAlgorithmChange field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1914 of file GlopParameters.java.

◆ hasBasisRefactorizationPeriod()

boolean com.google.ortools.glop.GlopParameters.hasBasisRefactorizationPeriod ( )

Number of iterations between two basis refactorizations. Note that various
conditions in the algorithm may trigger a refactorization before this
period is reached. Set this to 0 if you want to refactorize at each step.

optional int32 basis_refactorization_period = 19 [default = 64];

Returns: Whether the basisRefactorizationPeriod field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1409 of file GlopParameters.java.

◆ hasChangeStatusToImprecise()

boolean com.google.ortools.glop.GlopParameters.hasChangeStatusToImprecise ( )

If true, the internal API will change the return status to imprecise if the
solution does not respect the internal tolerances.

optional bool change_status_to_imprecise = 58 [default = true];

Returns: Whether the changeStatusToImprecise field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1637 of file GlopParameters.java.

◆ hasCostScaling()

boolean com.google.ortools.glop.GlopParameters.hasCostScaling ( )

optional .operations_research.glop.GlopParameters.CostScalingAlgorithm cost_scaling = 60 [default = CONTAIN_ONE_COST_SCALING];

Returns: Whether the costScaling field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1325 of file GlopParameters.java.

◆ hasCrossoverBoundSnappingDistance()

boolean com.google.ortools.glop.GlopParameters.hasCrossoverBoundSnappingDistance ( )

If the starting basis contains FREE variable with bounds, we will move
any such variable to their closer bounds if the distance is smaller than
this parameter.

The starting statuses can contains FREE variables with bounds, if a user
set it like this externally. Also, any variable with an initial BASIC
status that was not kept in the initial basis is marked as FREE before this
step is applied.

Note that by default a FREE variable is assumed to be zero unless a
starting value was specified via SetStartingVariableValuesForNextSolve().

Note that, at the end of the solve, some of these FREE variable with bounds
and an interior point value might still be left in the final solution.
Enable push_to_vertex to clean these up.

optional double crossover_bound_snapping_distance = 64 [default = inf];

Returns: Whether the crossoverBoundSnappingDistance field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2599 of file GlopParameters.java.

◆ hasDegenerateMinistepFactor()

boolean com.google.ortools.glop.GlopParameters.hasDegenerateMinistepFactor ( )

During a degenerate iteration, the more conservative approach is to do a
step of length zero (while shifting the bound of the leaving variable).
That is, the variable values are unchanged for the primal simplex or the
reduced cost are unchanged for the dual simplex. However, instead of doing
a step of length zero, it seems to be better on degenerate problems to do a
small positive step. This is what is recommended in the EXPAND procedure
described in:
P. E. Gill, W. Murray, M. A. Saunders, and M. H. Wright. "A practical anti-
cycling procedure for linearly constrained optimization".
Mathematical Programming, 45:437&#92;u2013474, 1989.

Here, during a degenerate iteration we do a small positive step of this
factor times the primal (resp. dual) tolerance. In the primal simplex, this
may effectively push variable values (very slightly) further out of their
bounds (resp. reduced costs for the dual simplex).

Setting this to zero reverts to the more conservative approach of a zero
step during degenerate iterations.

optional double degenerate_ministep_factor = 42 [default = 0.01];

Returns: Whether the degenerateMinistepFactor field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2242 of file GlopParameters.java.

◆ hasDevexWeightsResetPeriod()

boolean com.google.ortools.glop.GlopParameters.hasDevexWeightsResetPeriod ( )

Devex weights will be reset to 1.0 after that number of updates.

optional int32 devex_weights_reset_period = 33 [default = 150];

Returns: Whether the devexWeightsResetPeriod field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1944 of file GlopParameters.java.

◆ hasDropMagnitude()

boolean com.google.ortools.glop.GlopParameters.hasDropMagnitude ( )

Value in the input LP lower than this will be ignored. This is similar to
drop_tolerance but more aggressive as this is used before scaling. This is
mainly here to avoid underflow and have simpler invariant in the code, like
a * b == 0 iff a or b is zero and things like this.

optional double drop_magnitude = 71 [default = 1e-30];

Returns: Whether the dropMagnitude field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2744 of file GlopParameters.java.

◆ hasDropTolerance()

boolean com.google.ortools.glop.GlopParameters.hasDropTolerance ( )

In order to increase the sparsity of the manipulated vectors, floating
point values with a magnitude smaller than this parameter are set to zero
(only in some places). This parameter should be positive or zero.

optional double drop_tolerance = 52 [default = 1e-14];

Returns: Whether the dropTolerance field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1272 of file GlopParameters.java.

◆ hasDualFeasibilityTolerance()

boolean com.google.ortools.glop.GlopParameters.hasDualFeasibilityTolerance ( )

Variables whose reduced costs have an absolute value smaller than this
tolerance are not considered as entering candidates. That is they do not
take part in deciding whether a solution is dual-feasible or not.

Note that this value can temporarily increase during the execution of the
algorithm if the estimated precision of the reduced costs is higher than
this tolerance. Note also that we scale the costs (in the presolve step) so
that the cost magnitude range contains one.

This is also known as the optimality tolerance in other solvers.

optional double dual_feasibility_tolerance = 11 [default = 1e-08];

Returns: Whether the dualFeasibilityTolerance field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1088 of file GlopParameters.java.

◆ hasDualizerThreshold()

boolean com.google.ortools.glop.GlopParameters.hasDualizerThreshold ( )

When solve_dual_problem is LET_SOLVER_DECIDE, take the dual if the number
of constraints of the problem is more than this threshold times the number
of variables.

optional double dualizer_threshold = 21 [default = 1.5];

Returns: Whether the dualizerThreshold field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1505 of file GlopParameters.java.

◆ hasDualPricePrioritizeNorm()

boolean com.google.ortools.glop.GlopParameters.hasDualPricePrioritizeNorm ( )

On some problem like stp3d or pds-100 this makes a huge difference in
speed and number of iterations of the dual simplex.

optional bool dual_price_prioritize_norm = 69 [default = false];

Returns: Whether the dualPricePrioritizeNorm field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2775 of file GlopParameters.java.

◆ hasDualSmallPivotThreshold()

boolean com.google.ortools.glop.GlopParameters.hasDualSmallPivotThreshold ( )

Like small_pivot_threshold but for the dual simplex. This is needed because
the dual algorithm does not interpret this value in the same way.
TODO(user): Clean this up and use the same small pivot detection.

optional double dual_small_pivot_threshold = 38 [default = 0.0001];

Returns: Whether the dualSmallPivotThreshold field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2097 of file GlopParameters.java.

◆ hasDynamicallyAdjustRefactorizationPeriod()

boolean com.google.ortools.glop.GlopParameters.hasDynamicallyAdjustRefactorizationPeriod ( )

If this is true, then basis_refactorization_period becomes a lower bound on
the number of iterations between two refactorization (provided there is no
numerical accuracy issues). Depending on the estimated time to refactorize
vs the extra time spend in each solves because of the LU update, we try to
balance the two times.

optional bool dynamically_adjust_refactorization_period = 63 [default = true];

Returns: Whether the dynamicallyAdjustRefactorizationPeriod field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1442 of file GlopParameters.java.

◆ hasExploitSingletonColumnInInitialBasis()

boolean com.google.ortools.glop.GlopParameters.hasExploitSingletonColumnInInitialBasis ( )

Whether or not we exploit the singleton columns already present in the
problem when we create the initial basis.

optional bool exploit_singleton_column_in_initial_basis = 37 [default = true];

Returns: Whether the exploitSingletonColumnInInitialBasis field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2067 of file GlopParameters.java.

◆ hasFeasibilityRule()

boolean com.google.ortools.glop.GlopParameters.hasFeasibilityRule ( )

PricingRule to use during the feasibility phase.

optional .operations_research.glop.GlopParameters.PricingRule feasibility_rule = 1 [default = STEEPEST_EDGE];

Returns: Whether the feasibilityRule field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 880 of file GlopParameters.java.

◆ hasHarrisToleranceRatio()

boolean com.google.ortools.glop.GlopParameters.hasHarrisToleranceRatio ( )

This impacts the ratio test and indicates by how much we allow a basic
variable value that we move to go out of bounds. The value should be in
[0.0, 1.0) and should be interpreted as a ratio of the
primal_feasibility_tolerance. Setting this to 0.0 basically disables the
Harris ratio test while setting this too close to 1.0 will make it
difficult to keep the variable values inside their bounds modulo the
primal_feasibility_tolerance.

Note that the same comment applies to the dual simplex ratio test. There,
we allow the reduced costs to be of an infeasible sign by as much as this
ratio times the dual_feasibility_tolerance.

optional double harris_tolerance_ratio = 13 [default = 0.5];

Returns: Whether the harrisToleranceRatio field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1173 of file GlopParameters.java.

◆ hashCode()

int com.google.ortools.glop.GlopParameters.hashCode ( )

Definition at line 3553 of file GlopParameters.java.

◆ hasInitialBasis()

boolean com.google.ortools.glop.GlopParameters.hasInitialBasis ( )

What heuristic is used to try to replace the fixed slack columns in the
initial basis of the primal simplex.

optional .operations_research.glop.GlopParameters.InitialBasisHeuristic initial_basis = 17 [default = TRIANGULAR];

Returns: Whether the initialBasis field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1348 of file GlopParameters.java.

◆ hasInitialConditionNumberThreshold()

boolean com.google.ortools.glop.GlopParameters.hasInitialConditionNumberThreshold ( )

If our upper bound on the condition number of the initial basis (from our
heurisitic or a warm start) is above this threshold, we revert to an all
slack basis.

optional double initial_condition_number_threshold = 59 [default = 1e+50];

Returns: Whether the initialConditionNumberThreshold field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2498 of file GlopParameters.java.

◆ hasInitializeDevexWithColumnNorms()

boolean com.google.ortools.glop.GlopParameters.hasInitializeDevexWithColumnNorms ( )

Whether we initialize devex weights to 1.0 or to the norms of the matrix
columns.

optional bool initialize_devex_with_column_norms = 36 [default = true];

Returns: Whether the initializeDevexWithColumnNorms field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2038 of file GlopParameters.java.

◆ hasLogSearchProgress()

boolean com.google.ortools.glop.GlopParameters.hasLogSearchProgress ( )

If true, logs the progress of a solve to LOG(INFO). Note that the same
messages can also be turned on by displaying logs at level 1 for the
relevant files.

optional bool log_search_progress = 61 [default = false];

Returns: Whether the logSearchProgress field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2529 of file GlopParameters.java.

◆ hasLogToStdout()

boolean com.google.ortools.glop.GlopParameters.hasLogToStdout ( )

If true, logs will be displayed to stdout instead of using Google log info.

optional bool log_to_stdout = 66 [default = true];

Returns: Whether the logToStdout field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2558 of file GlopParameters.java.

◆ hasLuFactorizationPivotThreshold()

boolean com.google.ortools.glop.GlopParameters.hasLuFactorizationPivotThreshold ( )

Threshold for LU-factorization: for stability reasons, the magnitude of the
chosen pivot at a given step is guaranteed to be greater than this
threshold times the maximum magnitude of all the possible pivot choices in
the same column. The value must be in [0,1].

optional double lu_factorization_pivot_threshold = 25 [default = 0.01];

Returns: Whether the luFactorizationPivotThreshold field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1701 of file GlopParameters.java.

◆ hasMarkowitzSingularityThreshold()

boolean com.google.ortools.glop.GlopParameters.hasMarkowitzSingularityThreshold ( )

If a pivot magnitude is smaller than this during the Markowitz LU
factorization, then the matrix is assumed to be singular. Note that
this is an absolute threshold and is not relative to the other possible
pivots on the same column (see lu_factorization_pivot_threshold).

optional double markowitz_singularity_threshold = 30 [default = 1e-15];

Returns: Whether the markowitzSingularityThreshold field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1854 of file GlopParameters.java.

◆ hasMarkowitzZlatevParameter()

boolean com.google.ortools.glop.GlopParameters.hasMarkowitzZlatevParameter ( )

How many columns do we look at in the Markowitz pivoting rule to find
a good pivot. See markowitz.h.

optional int32 markowitz_zlatev_parameter = 29 [default = 3];

Returns: Whether the markowitzZlatevParameter field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1823 of file GlopParameters.java.

◆ hasMaxDeterministicTime()

boolean com.google.ortools.glop.GlopParameters.hasMaxDeterministicTime ( )

Maximum deterministic time allowed to solve a problem. The deterministic
time is more or less correlated to the running time, and its unit should
be around the second (at least on a Xeon(R) CPU E5-1650 v2 &#64; 3.50GHz).

TODO(user): Improve the correlation.

optional double max_deterministic_time = 45 [default = inf];

Returns: Whether the maxDeterministicTime field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1762 of file GlopParameters.java.

◆ hasMaxNumberOfIterations()

boolean com.google.ortools.glop.GlopParameters.hasMaxNumberOfIterations ( )

Maximum number of simplex iterations to solve a problem.
A value of -1 means no limit.

optional int64 max_number_of_iterations = 27 [default = -1];

Returns: Whether the maxNumberOfIterations field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1794 of file GlopParameters.java.

◆ hasMaxNumberOfReoptimizations()

boolean com.google.ortools.glop.GlopParameters.hasMaxNumberOfReoptimizations ( )

When the solution of phase II is imprecise, we re-run the phase II with the
opposite algorithm from that imprecise solution (i.e., if primal or dual
simplex was used, we use dual or primal simplex, respectively). We repeat
such re-optimization until the solution is precise, or we hit this limit.

optional double max_number_of_reoptimizations = 56 [default = 40];

Returns: Whether the maxNumberOfReoptimizations field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1668 of file GlopParameters.java.

◆ hasMaxTimeInSeconds()

boolean com.google.ortools.glop.GlopParameters.hasMaxTimeInSeconds ( )

Maximum time allowed in seconds to solve a problem.

optional double max_time_in_seconds = 26 [default = inf];

Returns: Whether the maxTimeInSeconds field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1731 of file GlopParameters.java.

◆ hasMaxValidMagnitude()

boolean com.google.ortools.glop.GlopParameters.hasMaxValidMagnitude ( )

Any finite values in the input LP 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. In practice, users
shouldn't use super large values in an LP. With the default threshold, even
evaluating large constraint with variables at their bound shouldn't cause
any overflow.

optional double max_valid_magnitude = 70 [default = 1e+30];

Returns: Whether the maxValidMagnitude field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2709 of file GlopParameters.java.

◆ hasMinimumAcceptablePivot()

boolean com.google.ortools.glop.GlopParameters.hasMinimumAcceptablePivot ( )

We never follow a basis change with a pivot under this threshold.

optional double minimum_acceptable_pivot = 15 [default = 1e-06];

Returns: Whether the minimumAcceptablePivot field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1243 of file GlopParameters.java.

◆ hasNumOmpThreads()

boolean com.google.ortools.glop.GlopParameters.hasNumOmpThreads ( )

Number of threads in the OMP parallel sections. If left to 1, the code will
not create any OMP threads and will remain single-threaded.

optional int32 num_omp_threads = 44 [default = 1];

Returns: Whether the numOmpThreads field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2342 of file GlopParameters.java.

◆ hasObjectiveLowerLimit()

boolean com.google.ortools.glop.GlopParameters.hasObjectiveLowerLimit ( )

The solver will stop as soon as it has proven that the objective is smaller
than objective_lower_limit or greater than objective_upper_limit. Depending
on the simplex algorithm (primal or dual) and the optimization direction,
note that only one bound will be used at the time.

Important: The solver does not add any tolerances to these values, and as
soon as the objective (as computed by the solver, so with some imprecision)
crosses one of these bounds (strictly), the search will stop. It is up to
the client to add any tolerance if needed.

optional double objective_lower_limit = 40 [default = -inf];

Returns: Whether the objectiveLowerLimit field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2171 of file GlopParameters.java.

◆ hasObjectiveUpperLimit()

boolean com.google.ortools.glop.GlopParameters.hasObjectiveUpperLimit ( )

optional double objective_upper_limit = 41 [default = inf];

Returns: Whether the objectiveUpperLimit field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2202 of file GlopParameters.java.

◆ hasOptimizationRule()

boolean com.google.ortools.glop.GlopParameters.hasOptimizationRule ( )

PricingRule to use during the optimization phase.

optional .operations_research.glop.GlopParameters.PricingRule optimization_rule = 2 [default = STEEPEST_EDGE];

Returns: Whether the optimizationRule field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 906 of file GlopParameters.java.

◆ hasPerturbCostsInDualSimplex()

boolean com.google.ortools.glop.GlopParameters.hasPerturbCostsInDualSimplex ( )

When this is true, then the costs are randomly perturbed before the dual
simplex is even started. This has been shown to improve the dual simplex
performance. For a good reference, see Huangfu Q (2013) "High performance
simplex solver", Ph.D, dissertation, University of Edinburgh.

optional bool perturb_costs_in_dual_simplex = 53 [default = false];

Returns: Whether the perturbCostsInDualSimplex field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2373 of file GlopParameters.java.

◆ hasPreprocessorZeroTolerance()

boolean com.google.ortools.glop.GlopParameters.hasPreprocessorZeroTolerance ( )

A floating point tolerance used by the preprocessors. This is used for
things like detecting if two columns/rows are proportional or if an
interval is empty.

Note that the preprocessors also use solution_feasibility_tolerance() to
detect if a problem is infeasible.

optional double preprocessor_zero_tolerance = 39 [default = 1e-09];

Returns: Whether the preprocessorZeroTolerance field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2131 of file GlopParameters.java.

◆ hasPrimalFeasibilityTolerance()

boolean com.google.ortools.glop.GlopParameters.hasPrimalFeasibilityTolerance ( )

This tolerance indicates by how much we allow the variable values to go out
of bounds and still consider the current solution primal-feasible. We also
use the same tolerance for the error A.x - b. Note that the two errors are
closely related if A is scaled in such a way that the greatest coefficient
magnitude on each column is 1.0.

This is also simply called feasibility tolerance in other solvers.

optional double primal_feasibility_tolerance = 10 [default = 1e-08];

Returns: Whether the primalFeasibilityTolerance field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1046 of file GlopParameters.java.

◆ hasProvideStrongOptimalGuarantee()

boolean com.google.ortools.glop.GlopParameters.hasProvideStrongOptimalGuarantee ( )

If true, then when the solver returns a solution with an OPTIMAL status,
we can guarantee that:
- The primal variable are in their bounds.
- The dual variable are in their bounds.
- If we modify each component of the right-hand side a bit and each
component of the objective function a bit, then the pair (primal values,
dual values) is an EXACT optimal solution of the perturbed problem.
- The modifications above are smaller than the associated tolerances as
defined in the comment for solution_feasibility_tolerance (*).

(*): This is the only place where the guarantee is not tight since we
compute the upper bounds with scalar product of the primal/dual
solution and the initial problem coefficients with only double precision.

Note that whether or not this option is true, we still check the
primal/dual infeasibility and objective gap. However if it is false, we
don't move the primal/dual values within their bounds and leave them
untouched.

optional bool provide_strong_optimal_guarantee = 24 [default = true];

Returns: Whether the provideStrongOptimalGuarantee field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1592 of file GlopParameters.java.

◆ hasPushToVertex()

boolean com.google.ortools.glop.GlopParameters.hasPushToVertex ( )

If the optimization phases finishes with super-basic variables (i.e.,
variables that either 1) have bounds but are FREE in the basis, or 2) have
no bounds and are FREE in the basis at a nonzero value), then run a "push"
phase to push these variables to bounds, obtaining a vertex solution. Note
this situation can happen only if a starting value was specified via
SetStartingVariableValuesForNextSolve().

optional bool push_to_vertex = 65 [default = true];

Returns: Whether the pushToVertex field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2645 of file GlopParameters.java.

◆ hasRandomSeed()

boolean com.google.ortools.glop.GlopParameters.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.
Note that this may lead to a different solution, for example a different
optimal basis.

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.

Also note that the solver is fully deterministic: two runs of the same
binary, on the same machine, on the exact same data and with the same
parameters will go through the exact same iterations. If they hit a time
limit, they might of course yield different results because one will have
advanced farther than the other.

optional int32 random_seed = 43 [default = 1];

Returns: Whether the randomSeed field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2300 of file GlopParameters.java.

◆ hasRatioTestZeroThreshold()

boolean com.google.ortools.glop.GlopParameters.hasRatioTestZeroThreshold ( )

During the primal simplex (resp. dual simplex), the coefficients of the
direction (resp. update row) with a magnitude lower than this threshold are
not considered during the ratio test. This tolerance is related to the
precision at which a Solve() involving the basis matrix can be performed.

TODO(user): Automatically increase it when we detect that the precision
of the Solve() is worse than this.

optional double ratio_test_zero_threshold = 12 [default = 1e-09];

Returns: Whether the ratioTestZeroThreshold field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1130 of file GlopParameters.java.

◆ hasRecomputeEdgesNormThreshold()

boolean com.google.ortools.glop.GlopParameters.hasRecomputeEdgesNormThreshold ( )

Note that the threshold is a relative error on the actual norm (not the
squared one) and that edge norms are always greater than 1. Recomputing
norms is a really expensive operation and a large threshold is ok since
this doesn't impact directly the solution but just the entering variable
choice.

optional double recompute_edges_norm_threshold = 9 [default = 100];

Returns: Whether the recomputeEdgesNormThreshold field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1009 of file GlopParameters.java.

◆ hasRecomputeReducedCostsThreshold()

boolean com.google.ortools.glop.GlopParameters.hasRecomputeReducedCostsThreshold ( )

We estimate the accuracy of the iteratively computed reduced costs. If
it falls below this threshold, we reinitialize them from scratch. Note
that such an operation is pretty fast, so we can use a low threshold.
It is important to have a good accuracy here (better than the
dual_feasibility_tolerance below) to be sure of the sign of such a cost.

optional double recompute_reduced_costs_threshold = 8 [default = 1e-08];

Returns: Whether the recomputeReducedCostsThreshold field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 974 of file GlopParameters.java.

◆ hasRefactorizationThreshold()

boolean com.google.ortools.glop.GlopParameters.hasRefactorizationThreshold ( )

We estimate the factorization accuracy of B during each pivot by using
the fact that we can compute the pivot coefficient in two ways:
- From direction[leaving_row].
- From update_row[entering_column].
If the two values have a relative difference above this threshold, we
trigger a refactorization.

optional double refactorization_threshold = 6 [default = 1e-09];

Returns: Whether the refactorizationThreshold field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 938 of file GlopParameters.java.

◆ hasRelativeCostPerturbation()

boolean com.google.ortools.glop.GlopParameters.hasRelativeCostPerturbation ( )

The magnitude of the cost perturbation is given by
RandomIn(1.0, 2.0) * (
relative_cost_perturbation * cost
+ relative_max_cost_perturbation * max_cost);

optional double relative_cost_perturbation = 54 [default = 1e-05];

Returns: Whether the relativeCostPerturbation field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2447 of file GlopParameters.java.

◆ hasRelativeMaxCostPerturbation()

boolean com.google.ortools.glop.GlopParameters.hasRelativeMaxCostPerturbation ( )

optional double relative_max_cost_perturbation = 55 [default = 1e-07];

Returns: Whether the relativeMaxCostPerturbation field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2473 of file GlopParameters.java.

◆ hasScalingMethod()

boolean com.google.ortools.glop.GlopParameters.hasScalingMethod ( )

optional .operations_research.glop.GlopParameters.ScalingAlgorithm scaling_method = 57 [default = EQUILIBRATION];

Returns: Whether the scalingMethod field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 858 of file GlopParameters.java.

◆ hasSmallPivotThreshold()

boolean com.google.ortools.glop.GlopParameters.hasSmallPivotThreshold ( )

When we choose the leaving variable, we want to avoid small pivot because
they are the less precise and may cause numerical instabilities. For a
pivot under this threshold times the infinity norm of the direction, we try
various countermeasures in order to avoid using it.

optional double small_pivot_threshold = 14 [default = 1e-06];

Returns: Whether the smallPivotThreshold field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1213 of file GlopParameters.java.

◆ hasSolutionFeasibilityTolerance()

boolean com.google.ortools.glop.GlopParameters.hasSolutionFeasibilityTolerance ( )

When the problem status is OPTIMAL, we check the optimality using this
relative tolerance and change the status to IMPRECISE if an issue is
detected.

The tolerance is "relative" in the sense that our thresholds are:
- tolerance * max(1.0, abs(bound)) for crossing a given bound.
- tolerance * max(1.0, abs(cost)) for an infeasible reduced cost.
- tolerance for an infeasible dual value.

optional double solution_feasibility_tolerance = 22 [default = 1e-06];

Returns: Whether the solutionFeasibilityTolerance field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1541 of file GlopParameters.java.

◆ hasSolveDualProblem()

boolean com.google.ortools.glop.GlopParameters.hasSolveDualProblem ( )

Whether or not we solve the dual of the given problem.
With a value of auto, the algorithm decide which approach is probably the
fastest depending on the problem dimensions (see dualizer_threshold).

optional .operations_research.glop.GlopParameters.SolverBehavior solve_dual_problem = 20 [default = LET_SOLVER_DECIDE];

Returns: Whether the solveDualProblem field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1474 of file GlopParameters.java.

◆ hasUseDedicatedDualFeasibilityAlgorithm()

boolean com.google.ortools.glop.GlopParameters.hasUseDedicatedDualFeasibilityAlgorithm ( )

We have two possible dual phase I algorithms. Both work on an LP that
minimize the sum of dual infeasiblities. One use dedicated code (when this
param is true), the other one use exactly the same code as the dual phase
II but on an auxiliary problem where the variable bounds of the original
problem are changed.

TODO(user): For now we have both, but ideally the non-dedicated version
will win since it is a lot less code to maintain.

optional bool use_dedicated_dual_feasibility_algorithm = 62 [default = true];

Returns: Whether the useDedicatedDualFeasibilityAlgorithm field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2410 of file GlopParameters.java.

◆ hasUseDualSimplex()

boolean com.google.ortools.glop.GlopParameters.hasUseDualSimplex ( )

Whether or not we use the dual simplex algorithm instead of the primal.

optional bool use_dual_simplex = 31 [default = false];

Returns: Whether the useDualSimplex field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1884 of file GlopParameters.java.

◆ hasUseImpliedFreePreprocessor()

boolean com.google.ortools.glop.GlopParameters.hasUseImpliedFreePreprocessor ( )

If presolve runs, include the pass that detects implied free variables.

optional bool use_implied_free_preprocessor = 67 [default = true];

Returns: Whether the useImpliedFreePreprocessor field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2677 of file GlopParameters.java.

◆ hasUseMiddleProductFormUpdate()

boolean com.google.ortools.glop.GlopParameters.hasUseMiddleProductFormUpdate ( )

Whether or not to use the middle product form update rather than the
standard eta LU update. The middle form product update should be a lot more
efficient (close to the Forrest-Tomlin update, a bit slower but easier to
implement). See for more details:
Qi Huangfu, J. A. Julian Hall, "Novel update techniques for the revised
simplex method", 28 january 2013, Technical Report ERGO-13-0001
http://www.maths.ed.ac.uk/hall/HuHa12/ERGO-13-001.pdf

optional bool use_middle_product_form_update = 35 [default = true];

Returns: Whether the useMiddleProductFormUpdate field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 2004 of file GlopParameters.java.

◆ hasUsePreprocessing()

boolean com.google.ortools.glop.GlopParameters.hasUsePreprocessing ( )

Whether or not we use advanced preprocessing techniques.

optional bool use_preprocessing = 34 [default = true];

Returns: Whether the usePreprocessing field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1971 of file GlopParameters.java.

◆ hasUseScaling()

boolean com.google.ortools.glop.GlopParameters.hasUseScaling ( )

Whether or not we scale the matrix A so that the maximum coefficient on
each line and each column is 1.0.

optional bool use_scaling = 16 [default = true];

Returns: Whether the useScaling field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1302 of file GlopParameters.java.

◆ hasUseTransposedMatrix()

boolean com.google.ortools.glop.GlopParameters.hasUseTransposedMatrix ( )

Whether or not we keep a transposed version of the matrix A to speed-up the
pricing at the cost of extra memory and the initial tranposition
computation.

optional bool use_transposed_matrix = 18 [default = true];

Returns: Whether the useTransposedMatrix field is set.

Implements com.google.ortools.glop.GlopParametersOrBuilder.

Definition at line 1378 of file GlopParameters.java.

◆ internalGetFieldAccessorTable()

com.google.protobuf.GeneratedMessage.FieldAccessorTable com.google.ortools.glop.GlopParameters.internalGetFieldAccessorTable ( )

protected

Definition at line 96 of file GlopParameters.java.

◆ isInitialized()

final boolean com.google.ortools.glop.GlopParameters.isInitialized ( )

Definition at line 2794 of file GlopParameters.java.

◆ newBuilder() [1/2]

static Builder com.google.ortools.glop.GlopParameters.newBuilder ( )

static

Definition at line 3917 of file GlopParameters.java.

◆ newBuilder() [2/2]

static Builder com.google.ortools.glop.GlopParameters.newBuilder ( com.google.ortools.glop.GlopParameters prototype )

static

Definition at line 3920 of file GlopParameters.java.

◆ newBuilderForType() [1/2]

Builder com.google.ortools.glop.GlopParameters.newBuilderForType ( )

Definition at line 3916 of file GlopParameters.java.

◆ newBuilderForType() [2/2]

Builder com.google.ortools.glop.GlopParameters.newBuilderForType ( com.google.protobuf.GeneratedMessage.BuilderParent parent )

protected

Definition at line 3930 of file GlopParameters.java.

◆ parseDelimitedFrom() [1/2]

static com.google.ortools.glop.GlopParameters com.google.ortools.glop.GlopParameters.parseDelimitedFrom ( java.io.InputStream input ) throws java.io.IOException

static

Definition at line 3888 of file GlopParameters.java.

◆ parseDelimitedFrom() [2/2]

static com.google.ortools.glop.GlopParameters com.google.ortools.glop.GlopParameters.parseDelimitedFrom	(	java.io.InputStream	input,
		com.google.protobuf.ExtensionRegistryLite	extensionRegistry ) throws java.io.IOException

static

Definition at line 3894 of file GlopParameters.java.

◆ parseFrom() [1/10]

static com.google.ortools.glop.GlopParameters com.google.ortools.glop.GlopParameters.parseFrom ( byte[] data ) throws com.google.protobuf.InvalidProtocolBufferException

static

Definition at line 3865 of file GlopParameters.java.

◆ parseFrom() [2/10]

static com.google.ortools.glop.GlopParameters com.google.ortools.glop.GlopParameters.parseFrom	(	byte[]	data,
		com.google.protobuf.ExtensionRegistryLite	extensionRegistry ) throws com.google.protobuf.InvalidProtocolBufferException

static

Definition at line 3869 of file GlopParameters.java.

◆ parseFrom() [3/10]

static com.google.ortools.glop.GlopParameters com.google.ortools.glop.GlopParameters.parseFrom ( com.google.protobuf.ByteString data ) throws com.google.protobuf.InvalidProtocolBufferException

static

Definition at line 3854 of file GlopParameters.java.

◆ parseFrom() [4/10]

static com.google.ortools.glop.GlopParameters com.google.ortools.glop.GlopParameters.parseFrom	(	com.google.protobuf.ByteString	data,
		com.google.protobuf.ExtensionRegistryLite	extensionRegistry ) throws com.google.protobuf.InvalidProtocolBufferException

static

Definition at line 3859 of file GlopParameters.java.

◆ parseFrom() [5/10]

static com.google.ortools.glop.GlopParameters com.google.ortools.glop.GlopParameters.parseFrom ( com.google.protobuf.CodedInputStream input ) throws java.io.IOException

static

Definition at line 3901 of file GlopParameters.java.

◆ parseFrom() [6/10]

static com.google.ortools.glop.GlopParameters com.google.ortools.glop.GlopParameters.parseFrom	(	com.google.protobuf.CodedInputStream	input,
		com.google.protobuf.ExtensionRegistryLite	extensionRegistry ) throws java.io.IOException

static

Definition at line 3907 of file GlopParameters.java.

◆ parseFrom() [7/10]

static com.google.ortools.glop.GlopParameters com.google.ortools.glop.GlopParameters.parseFrom ( java.io.InputStream input ) throws java.io.IOException

static

Definition at line 3875 of file GlopParameters.java.

◆ parseFrom() [8/10]

static com.google.ortools.glop.GlopParameters com.google.ortools.glop.GlopParameters.parseFrom	(	java.io.InputStream	input,
		com.google.protobuf.ExtensionRegistryLite	extensionRegistry ) throws java.io.IOException

static

Definition at line 3880 of file GlopParameters.java.

◆ parseFrom() [9/10]

static com.google.ortools.glop.GlopParameters com.google.ortools.glop.GlopParameters.parseFrom ( java.nio.ByteBuffer data ) throws com.google.protobuf.InvalidProtocolBufferException

static

Definition at line 3843 of file GlopParameters.java.

◆ parseFrom() [10/10]

static com.google.ortools.glop.GlopParameters com.google.ortools.glop.GlopParameters.parseFrom	(	java.nio.ByteBuffer	data,
		com.google.protobuf.ExtensionRegistryLite	extensionRegistry ) throws com.google.protobuf.InvalidProtocolBufferException

static

Definition at line 3848 of file GlopParameters.java.

◆ parser()

static com.google.protobuf.Parser< GlopParameters > com.google.ortools.glop.GlopParameters.parser ( )

static

Definition at line 8925 of file GlopParameters.java.

◆ toBuilder()

Builder com.google.ortools.glop.GlopParameters.toBuilder ( )

Definition at line 3924 of file GlopParameters.java.

◆ writeTo()

void com.google.ortools.glop.GlopParameters.writeTo ( com.google.protobuf.CodedOutputStream output ) throws java.io.IOException

Definition at line 2804 of file GlopParameters.java.

Member Data Documentation

◆ ALLOW_SIMPLEX_ALGORITHM_CHANGE_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.ALLOW_SIMPLEX_ALGORITHM_CHANGE_FIELD_NUMBER = 32

static

Definition at line 1900 of file GlopParameters.java.

◆ BASIS_REFACTORIZATION_PERIOD_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.BASIS_REFACTORIZATION_PERIOD_FIELD_NUMBER = 19

static

Definition at line 1396 of file GlopParameters.java.

◆ CHANGE_STATUS_TO_IMPRECISE_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.CHANGE_STATUS_TO_IMPRECISE_FIELD_NUMBER = 58

static

Definition at line 1625 of file GlopParameters.java.

◆ COST_SCALING_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.COST_SCALING_FIELD_NUMBER = 60

static

Definition at line 1319 of file GlopParameters.java.

◆ CROSSOVER_BOUND_SNAPPING_DISTANCE_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.CROSSOVER_BOUND_SNAPPING_DISTANCE_FIELD_NUMBER = 64

static

Definition at line 2574 of file GlopParameters.java.

◆ DEGENERATE_MINISTEP_FACTOR_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.DEGENERATE_MINISTEP_FACTOR_FIELD_NUMBER = 42

static

Definition at line 2214 of file GlopParameters.java.

◆ DEVEX_WEIGHTS_RESET_PERIOD_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.DEVEX_WEIGHTS_RESET_PERIOD_FIELD_NUMBER = 33

static

Definition at line 1933 of file GlopParameters.java.

◆ DROP_MAGNITUDE_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.DROP_MAGNITUDE_FIELD_NUMBER = 71

static

Definition at line 2730 of file GlopParameters.java.

◆ DROP_TOLERANCE_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.DROP_TOLERANCE_FIELD_NUMBER = 52

static

Definition at line 1259 of file GlopParameters.java.

◆ DUAL_FEASIBILITY_TOLERANCE_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.DUAL_FEASIBILITY_TOLERANCE_FIELD_NUMBER = 11

static

Definition at line 1068 of file GlopParameters.java.

◆ DUAL_PRICE_PRIORITIZE_NORM_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.DUAL_PRICE_PRIORITIZE_NORM_FIELD_NUMBER = 69

static

Definition at line 2763 of file GlopParameters.java.

◆ DUAL_SMALL_PIVOT_THRESHOLD_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.DUAL_SMALL_PIVOT_THRESHOLD_FIELD_NUMBER = 38

static

Definition at line 2084 of file GlopParameters.java.

◆ DUALIZER_THRESHOLD_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.DUALIZER_THRESHOLD_FIELD_NUMBER = 21

static

Definition at line 1492 of file GlopParameters.java.

◆ DYNAMICALLY_ADJUST_REFACTORIZATION_PERIOD_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.DYNAMICALLY_ADJUST_REFACTORIZATION_PERIOD_FIELD_NUMBER = 63

static

Definition at line 1427 of file GlopParameters.java.

◆ EXPLOIT_SINGLETON_COLUMN_IN_INITIAL_BASIS_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.EXPLOIT_SINGLETON_COLUMN_IN_INITIAL_BASIS_FIELD_NUMBER = 37

static

Definition at line 2055 of file GlopParameters.java.

◆ FEASIBILITY_RULE_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.FEASIBILITY_RULE_FIELD_NUMBER = 1

static

Definition at line 870 of file GlopParameters.java.

◆ HARRIS_TOLERANCE_RATIO_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.HARRIS_TOLERANCE_RATIO_FIELD_NUMBER = 13

static

Definition at line 1152 of file GlopParameters.java.

◆ INITIAL_BASIS_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.INITIAL_BASIS_FIELD_NUMBER = 17

static

Definition at line 1337 of file GlopParameters.java.

◆ INITIAL_CONDITION_NUMBER_THRESHOLD_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.INITIAL_CONDITION_NUMBER_THRESHOLD_FIELD_NUMBER = 59

static

Definition at line 2485 of file GlopParameters.java.

◆ INITIALIZE_DEVEX_WITH_COLUMN_NORMS_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.INITIALIZE_DEVEX_WITH_COLUMN_NORMS_FIELD_NUMBER = 36

static

Definition at line 2026 of file GlopParameters.java.

◆ LOG_SEARCH_PROGRESS_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.LOG_SEARCH_PROGRESS_FIELD_NUMBER = 61

static

Definition at line 2516 of file GlopParameters.java.

◆ LOG_TO_STDOUT_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.LOG_TO_STDOUT_FIELD_NUMBER = 66

static

Definition at line 2547 of file GlopParameters.java.

◆ LU_FACTORIZATION_PIVOT_THRESHOLD_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.LU_FACTORIZATION_PIVOT_THRESHOLD_FIELD_NUMBER = 25

static

Definition at line 1687 of file GlopParameters.java.

◆ MARKOWITZ_SINGULARITY_THRESHOLD_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.MARKOWITZ_SINGULARITY_THRESHOLD_FIELD_NUMBER = 30

static

Definition at line 1840 of file GlopParameters.java.

◆ MARKOWITZ_ZLATEV_PARAMETER_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.MARKOWITZ_ZLATEV_PARAMETER_FIELD_NUMBER = 29

static

Definition at line 1811 of file GlopParameters.java.

◆ MAX_DETERMINISTIC_TIME_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.MAX_DETERMINISTIC_TIME_FIELD_NUMBER = 45

static

Definition at line 1747 of file GlopParameters.java.

◆ MAX_NUMBER_OF_ITERATIONS_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.MAX_NUMBER_OF_ITERATIONS_FIELD_NUMBER = 27

static

Definition at line 1782 of file GlopParameters.java.

◆ MAX_NUMBER_OF_REOPTIMIZATIONS_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.MAX_NUMBER_OF_REOPTIMIZATIONS_FIELD_NUMBER = 56

static

Definition at line 1654 of file GlopParameters.java.

◆ MAX_TIME_IN_SECONDS_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.MAX_TIME_IN_SECONDS_FIELD_NUMBER = 26

static

Definition at line 1720 of file GlopParameters.java.

◆ MAX_VALID_MAGNITUDE_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.MAX_VALID_MAGNITUDE_FIELD_NUMBER = 70

static

Definition at line 2693 of file GlopParameters.java.

◆ MINIMUM_ACCEPTABLE_PIVOT_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.MINIMUM_ACCEPTABLE_PIVOT_FIELD_NUMBER = 15

static

Definition at line 1232 of file GlopParameters.java.

◆ NUM_OMP_THREADS_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.NUM_OMP_THREADS_FIELD_NUMBER = 44

static

Definition at line 2330 of file GlopParameters.java.

◆ OBJECTIVE_LOWER_LIMIT_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.OBJECTIVE_LOWER_LIMIT_FIELD_NUMBER = 40

static

Definition at line 2152 of file GlopParameters.java.

◆ OBJECTIVE_UPPER_LIMIT_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.OBJECTIVE_UPPER_LIMIT_FIELD_NUMBER = 41

static

Definition at line 2195 of file GlopParameters.java.

◆ OPTIMIZATION_RULE_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.OPTIMIZATION_RULE_FIELD_NUMBER = 2

static

Definition at line 896 of file GlopParameters.java.

◆ PERTURB_COSTS_IN_DUAL_SIMPLEX_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.PERTURB_COSTS_IN_DUAL_SIMPLEX_FIELD_NUMBER = 53

static

Definition at line 2359 of file GlopParameters.java.

◆ PREPROCESSOR_ZERO_TOLERANCE_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.PREPROCESSOR_ZERO_TOLERANCE_FIELD_NUMBER = 39

static

Definition at line 2115 of file GlopParameters.java.

◆ PRIMAL_FEASIBILITY_TOLERANCE_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.PRIMAL_FEASIBILITY_TOLERANCE_FIELD_NUMBER = 10

static

Definition at line 1029 of file GlopParameters.java.

◆ PROVIDE_STRONG_OPTIMAL_GUARANTEE_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.PROVIDE_STRONG_OPTIMAL_GUARANTEE_FIELD_NUMBER = 24

static

Definition at line 1564 of file GlopParameters.java.

◆ PUSH_TO_VERTEX_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.PUSH_TO_VERTEX_FIELD_NUMBER = 65

static

Definition at line 2629 of file GlopParameters.java.

◆ RANDOM_SEED_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.RANDOM_SEED_FIELD_NUMBER = 43

static

Definition at line 2275 of file GlopParameters.java.

◆ RATIO_TEST_ZERO_THRESHOLD_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.RATIO_TEST_ZERO_THRESHOLD_FIELD_NUMBER = 12

static

Definition at line 1113 of file GlopParameters.java.

◆ RECOMPUTE_EDGES_NORM_THRESHOLD_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.RECOMPUTE_EDGES_NORM_THRESHOLD_FIELD_NUMBER = 9

static

Definition at line 994 of file GlopParameters.java.

◆ RECOMPUTE_REDUCED_COSTS_THRESHOLD_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.RECOMPUTE_REDUCED_COSTS_THRESHOLD_FIELD_NUMBER = 8

static

Definition at line 959 of file GlopParameters.java.

◆ REFACTORIZATION_THRESHOLD_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.REFACTORIZATION_THRESHOLD_FIELD_NUMBER = 6

static

Definition at line 922 of file GlopParameters.java.

◆ RELATIVE_COST_PERTURBATION_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.RELATIVE_COST_PERTURBATION_FIELD_NUMBER = 54

static

Definition at line 2433 of file GlopParameters.java.

◆ RELATIVE_MAX_COST_PERTURBATION_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.RELATIVE_MAX_COST_PERTURBATION_FIELD_NUMBER = 55

static

Definition at line 2466 of file GlopParameters.java.

◆ SCALING_METHOD_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.SCALING_METHOD_FIELD_NUMBER = 57

static

Definition at line 852 of file GlopParameters.java.

◆ SMALL_PIVOT_THRESHOLD_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.SMALL_PIVOT_THRESHOLD_FIELD_NUMBER = 14

static

Definition at line 1199 of file GlopParameters.java.

◆ SOLUTION_FEASIBILITY_TOLERANCE_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.SOLUTION_FEASIBILITY_TOLERANCE_FIELD_NUMBER = 22

static

Definition at line 1523 of file GlopParameters.java.

◆ SOLVE_DUAL_PROBLEM_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.SOLVE_DUAL_PROBLEM_FIELD_NUMBER = 20

static

Definition at line 1462 of file GlopParameters.java.

◆ USE_DEDICATED_DUAL_FEASIBILITY_ALGORITHM_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.USE_DEDICATED_DUAL_FEASIBILITY_ALGORITHM_FIELD_NUMBER = 62

static

Definition at line 2392 of file GlopParameters.java.

◆ USE_DUAL_SIMPLEX_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.USE_DUAL_SIMPLEX_FIELD_NUMBER = 31

static

Definition at line 1873 of file GlopParameters.java.

◆ USE_IMPLIED_FREE_PREPROCESSOR_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.USE_IMPLIED_FREE_PREPROCESSOR_FIELD_NUMBER = 67

static

Definition at line 2666 of file GlopParameters.java.

◆ USE_MIDDLE_PRODUCT_FORM_UPDATE_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.USE_MIDDLE_PRODUCT_FORM_UPDATE_FIELD_NUMBER = 35

static

Definition at line 1987 of file GlopParameters.java.

◆ USE_PREPROCESSING_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.USE_PREPROCESSING_FIELD_NUMBER = 34

static

Definition at line 1960 of file GlopParameters.java.

◆ USE_SCALING_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.USE_SCALING_FIELD_NUMBER = 16

static

Definition at line 1290 of file GlopParameters.java.

◆ USE_TRANSPOSED_MATRIX_FIELD_NUMBER

final int com.google.ortools.glop.GlopParameters.USE_TRANSPOSED_MATRIX_FIELD_NUMBER = 18

static

Definition at line 1365 of file GlopParameters.java.

The documentation for this class was generated from the following file:

build/java/ortools-java/src/main/java/com/google/ortools/glop/GlopParameters.java

Classes

Public Member Functions

Static Public Member Functions

Static Public Attributes

Protected Member Functions

Detailed Description

Member Function Documentation

◆ equals()

◆ getAllowSimplexAlgorithmChange()

◆ getBasisRefactorizationPeriod()

◆ getChangeStatusToImprecise()

◆ getCostScaling()

◆ getCrossoverBoundSnappingDistance()

◆ getDefaultInstance()

◆ getDefaultInstanceForType()

◆ getDegenerateMinistepFactor()

◆ getDescriptor()

◆ getDevexWeightsResetPeriod()

◆ getDropMagnitude()

◆ getDropTolerance()

◆ getDualFeasibilityTolerance()

◆ getDualizerThreshold()

◆ getDualPricePrioritizeNorm()

◆ getDualSmallPivotThreshold()

◆ getDynamicallyAdjustRefactorizationPeriod()

◆ getExploitSingletonColumnInInitialBasis()

◆ getFeasibilityRule()

◆ getHarrisToleranceRatio()

◆ getInitialBasis()

◆ getInitialConditionNumberThreshold()

◆ getInitializeDevexWithColumnNorms()

◆ getLogSearchProgress()

◆ getLogToStdout()

◆ getLuFactorizationPivotThreshold()

◆ getMarkowitzSingularityThreshold()

◆ getMarkowitzZlatevParameter()

◆ getMaxDeterministicTime()

◆ getMaxNumberOfIterations()

◆ getMaxNumberOfReoptimizations()

◆ getMaxTimeInSeconds()

◆ getMaxValidMagnitude()

◆ getMinimumAcceptablePivot()

◆ getNumOmpThreads()

◆ getObjectiveLowerLimit()

◆ getObjectiveUpperLimit()

◆ getOptimizationRule()

◆ getParserForType()

◆ getPerturbCostsInDualSimplex()

◆ getPreprocessorZeroTolerance()

◆ getPrimalFeasibilityTolerance()

◆ getProvideStrongOptimalGuarantee()

◆ getPushToVertex()

◆ getRandomSeed()

◆ getRatioTestZeroThreshold()

◆ getRecomputeEdgesNormThreshold()

◆ getRecomputeReducedCostsThreshold()

◆ getRefactorizationThreshold()

◆ getRelativeCostPerturbation()

◆ getRelativeMaxCostPerturbation()

◆ getScalingMethod()

◆ getSerializedSize()

◆ getSmallPivotThreshold()

◆ getSolutionFeasibilityTolerance()

◆ getSolveDualProblem()

◆ getUseDedicatedDualFeasibilityAlgorithm()

◆ getUseDualSimplex()

◆ getUseImpliedFreePreprocessor()

◆ getUseMiddleProductFormUpdate()

◆ getUsePreprocessing()

◆ getUseScaling()

◆ getUseTransposedMatrix()

◆ hasAllowSimplexAlgorithmChange()

◆ hasBasisRefactorizationPeriod()

◆ hasChangeStatusToImprecise()

◆ hasCostScaling()

◆ hasCrossoverBoundSnappingDistance()

◆ hasDegenerateMinistepFactor()

◆ hasDevexWeightsResetPeriod()

◆ hasDropMagnitude()

◆ hasDropTolerance()