Uses of Class
com.google.ortools.pdlp.PrimalDualHybridGradientParams.Builder

Packages that use PrimalDualHybridGradientParams.Builder

Package	Description
com.google.ortools.pdlp

Uses of PrimalDualHybridGradientParams.Builder in com.google.ortools.pdlp

Methods in com.google.ortools.pdlp that return PrimalDualHybridGradientParams.Builder

Modifier and Type	Method and Description
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.addAllRandomProjectionSeeds(java.lang.Iterable<? extends java.lang.Integer> values) Seeds for generating (pseudo-)random projections of iterates during termination checks.
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.addRandomProjectionSeeds(int value) Seeds for generating (pseudo-)random projections of iterates during termination checks.
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.clear()
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.clearAdaptiveLinesearchParameters() optional .operations_research.pdlp.AdaptiveLinesearchParams adaptive_linesearch_parameters = 18;
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.clearDiagonalQpTrustRegionSolverTolerance() The solve tolerance of the experimental trust region solver for diagonal QPs, controlling the accuracy of binary search over a one-dimensional scaling parameter.
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.clearHandleSomePrimalGradientsOnFiniteBoundsAsResiduals() See https://developers.google.com/optimization/lp/pdlp_math#treating_some_variable_bounds_as_infinite for a description of this flag.
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.clearInfiniteConstraintBoundThreshold() Constraint bounds with absolute value at least this threshold are replaced with infinities.
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.clearInitialPrimalWeight() The initial value of the primal weight (i.e., the ratio of primal and dual step sizes).
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.clearInitialStepSizeScaling() Scaling factor applied to the initial step size (all step sizes if linesearch_rule == CONSTANT_STEP_SIZE_RULE).
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.clearL2NormRescaling() If true, applies L_2 norm rescaling after the Ruiz rescaling.
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.clearLinesearchRule() Linesearch rule applied at each major iteration.
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.clearLInfRuizIterations() Number of L_infinity Ruiz rescaling iterations to apply to the constraint matrix.
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.clearLogIntervalSeconds() Time between iteration-level statistics logging (if `verbosity_level > 1`).
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.clearMajorIterationFrequency() The frequency at which extra work is performed to make major algorithmic decisions, e.g., performing restarts and updating the primal weight.
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.clearMalitskyPockParameters() optional .operations_research.pdlp.MalitskyPockParams malitsky_pock_parameters = 19;
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.clearNecessaryReductionForRestart() For ADAPTIVE_HEURISTIC only: A relative reduction in the potential function by this amount triggers a restart if, additionally, the quality of the iterates appears to be getting worse.
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.clearNumShards() For more efficient parallel computation, the matrices and vectors are divided (virtually) into num_shards shards.
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.clearNumThreads() The number of threads to use.
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.clearPresolveOptions() optional .operations_research.pdlp.PrimalDualHybridGradientParams.PresolveOptions presolve_options = 16;
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.clearPrimalWeightUpdateSmoothing() This parameter controls exponential smoothing of log(primal_weight) when a primal weight update occurs (i.e., when the ratio of primal and dual step sizes is adjusted).
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.clearRandomProjectionSeeds() Seeds for generating (pseudo-)random projections of iterates during termination checks.
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.clearRecordIterationStats() If true, the iteration_stats field of the SolveLog output will be populated at every iteration.
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.clearRestartStrategy() NO_RESTARTS and EVERY_MAJOR_ITERATION occasionally outperform the default.
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.clearSchedulerType() The type of scheduler used for CPU multi-threading.
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.clearSufficientReductionForRestart() For ADAPTIVE_HEURISTIC and ADAPTIVE_DISTANCE_BASED only: A relative reduction in the potential function by this amount always triggers a restart.
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.clearTerminationCheckFrequency() The frequency (based on a counter reset every major iteration) to check for termination (involves extra work) and log iteration stats.
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.clearTerminationCriteria() optional .operations_research.pdlp.TerminationCriteria termination_criteria = 1;
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.clearUseDiagonalQpTrustRegionSolver() When solving QPs with diagonal objective matrices, this option can be turned on to enable an experimental solver that avoids linearization of the quadratic term.
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.clearUseFeasibilityPolishing() If true, periodically runs feasibility polishing, which attempts to move from latest average iterate to one that is closer to feasibility (i.e., has smaller primal and dual residuals) while probably increasing the objective gap.
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.clearVerbosityLevel() The verbosity of logging. 0: No informational logging.
PrimalDualHybridGradientParams.Builder	SolveLog.Builder.getParamsBuilder() If solved with PDLP, the parameters for this solve.
PrimalDualHybridGradientParams.Builder	FeasibilityPolishingDetails.Builder.getParamsBuilder() optional .operations_research.pdlp.PrimalDualHybridGradientParams params = 3;
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.mergeAdaptiveLinesearchParameters(AdaptiveLinesearchParams value) optional .operations_research.pdlp.AdaptiveLinesearchParams adaptive_linesearch_parameters = 18;
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.mergeFrom(com.google.protobuf.Message other)
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.mergeFrom(PrimalDualHybridGradientParams other)
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.mergeMalitskyPockParameters(MalitskyPockParams value) optional .operations_research.pdlp.MalitskyPockParams malitsky_pock_parameters = 19;
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.mergePresolveOptions(PrimalDualHybridGradientParams.PresolveOptions value) optional .operations_research.pdlp.PrimalDualHybridGradientParams.PresolveOptions presolve_options = 16;
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.mergeTerminationCriteria(TerminationCriteria value) optional .operations_research.pdlp.TerminationCriteria termination_criteria = 1;
static PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.newBuilder()
static PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.newBuilder(PrimalDualHybridGradientParams prototype)
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.newBuilderForType()
protected PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.newBuilderForType(com.google.protobuf.AbstractMessage.BuilderParent parent)
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.setAdaptiveLinesearchParameters(AdaptiveLinesearchParams.Builder builderForValue) optional .operations_research.pdlp.AdaptiveLinesearchParams adaptive_linesearch_parameters = 18;
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.setAdaptiveLinesearchParameters(AdaptiveLinesearchParams value) optional .operations_research.pdlp.AdaptiveLinesearchParams adaptive_linesearch_parameters = 18;
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.setDiagonalQpTrustRegionSolverTolerance(double value) The solve tolerance of the experimental trust region solver for diagonal QPs, controlling the accuracy of binary search over a one-dimensional scaling parameter.
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.setHandleSomePrimalGradientsOnFiniteBoundsAsResiduals(boolean value) See https://developers.google.com/optimization/lp/pdlp_math#treating_some_variable_bounds_as_infinite for a description of this flag.
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.setInfiniteConstraintBoundThreshold(double value) Constraint bounds with absolute value at least this threshold are replaced with infinities.
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.setInitialPrimalWeight(double value) The initial value of the primal weight (i.e., the ratio of primal and dual step sizes).
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.setInitialStepSizeScaling(double value) Scaling factor applied to the initial step size (all step sizes if linesearch_rule == CONSTANT_STEP_SIZE_RULE).
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.setL2NormRescaling(boolean value) If true, applies L_2 norm rescaling after the Ruiz rescaling.
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.setLinesearchRule(PrimalDualHybridGradientParams.LinesearchRule value) Linesearch rule applied at each major iteration.
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.setLInfRuizIterations(int value) Number of L_infinity Ruiz rescaling iterations to apply to the constraint matrix.
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.setLogIntervalSeconds(double value) Time between iteration-level statistics logging (if `verbosity_level > 1`).
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.setMajorIterationFrequency(int value) The frequency at which extra work is performed to make major algorithmic decisions, e.g., performing restarts and updating the primal weight.
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.setMalitskyPockParameters(MalitskyPockParams.Builder builderForValue) optional .operations_research.pdlp.MalitskyPockParams malitsky_pock_parameters = 19;
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.setMalitskyPockParameters(MalitskyPockParams value) optional .operations_research.pdlp.MalitskyPockParams malitsky_pock_parameters = 19;
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.setNecessaryReductionForRestart(double value) For ADAPTIVE_HEURISTIC only: A relative reduction in the potential function by this amount triggers a restart if, additionally, the quality of the iterates appears to be getting worse.
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.setNumShards(int value) For more efficient parallel computation, the matrices and vectors are divided (virtually) into num_shards shards.
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.setNumThreads(int value) The number of threads to use.
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.setPresolveOptions(PrimalDualHybridGradientParams.PresolveOptions.Builder builderForValue) optional .operations_research.pdlp.PrimalDualHybridGradientParams.PresolveOptions presolve_options = 16;
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.setPresolveOptions(PrimalDualHybridGradientParams.PresolveOptions value) optional .operations_research.pdlp.PrimalDualHybridGradientParams.PresolveOptions presolve_options = 16;
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.setPrimalWeightUpdateSmoothing(double value) This parameter controls exponential smoothing of log(primal_weight) when a primal weight update occurs (i.e., when the ratio of primal and dual step sizes is adjusted).
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.setRandomProjectionSeeds(int index, int value) Seeds for generating (pseudo-)random projections of iterates during termination checks.
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.setRecordIterationStats(boolean value) If true, the iteration_stats field of the SolveLog output will be populated at every iteration.
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.setRestartStrategy(PrimalDualHybridGradientParams.RestartStrategy value) NO_RESTARTS and EVERY_MAJOR_ITERATION occasionally outperform the default.
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.setSchedulerType(SchedulerType value) The type of scheduler used for CPU multi-threading.
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.setSufficientReductionForRestart(double value) For ADAPTIVE_HEURISTIC and ADAPTIVE_DISTANCE_BASED only: A relative reduction in the potential function by this amount always triggers a restart.
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.setTerminationCheckFrequency(int value) The frequency (based on a counter reset every major iteration) to check for termination (involves extra work) and log iteration stats.
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.setTerminationCriteria(TerminationCriteria.Builder builderForValue) optional .operations_research.pdlp.TerminationCriteria termination_criteria = 1;
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.setTerminationCriteria(TerminationCriteria value) optional .operations_research.pdlp.TerminationCriteria termination_criteria = 1;
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.setUseDiagonalQpTrustRegionSolver(boolean value) When solving QPs with diagonal objective matrices, this option can be turned on to enable an experimental solver that avoids linearization of the quadratic term.
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.setUseFeasibilityPolishing(boolean value) If true, periodically runs feasibility polishing, which attempts to move from latest average iterate to one that is closer to feasibility (i.e., has smaller primal and dual residuals) while probably increasing the objective gap.
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.Builder.setVerbosityLevel(int value) The verbosity of logging. 0: No informational logging.
PrimalDualHybridGradientParams.Builder	PrimalDualHybridGradientParams.toBuilder()

Methods in com.google.ortools.pdlp with parameters of type PrimalDualHybridGradientParams.Builder

Modifier and Type	Method and Description
SolveLog.Builder	SolveLog.Builder.setParams(PrimalDualHybridGradientParams.Builder builderForValue) If solved with PDLP, the parameters for this solve.
FeasibilityPolishingDetails.Builder	FeasibilityPolishingDetails.Builder.setParams(PrimalDualHybridGradientParams.Builder builderForValue) optional .operations_research.pdlp.PrimalDualHybridGradientParams params = 3;