Inheritance diagram for com.google.ortools.pdlp.PrimalDualHybridGradientParams:

Classes
class	Builder

enum	LinesearchRule

class	PresolveOptions

interface	PresolveOptionsOrBuilder

enum	RestartStrategy

Public Member Functions
boolean	hasTerminationCriteria ()

com.google.ortools.pdlp.TerminationCriteria	getTerminationCriteria ()

com.google.ortools.pdlp.TerminationCriteriaOrBuilder	getTerminationCriteriaOrBuilder ()

boolean	hasNumThreads ()

int	getNumThreads ()

boolean	hasNumShards ()

int	getNumShards ()

boolean	hasSchedulerType ()

com.google.ortools.pdlp.SchedulerType	getSchedulerType ()

boolean	hasRecordIterationStats ()

boolean	getRecordIterationStats ()

boolean	hasVerbosityLevel ()

int	getVerbosityLevel ()

boolean	hasLogIntervalSeconds ()

double	getLogIntervalSeconds ()

boolean	hasMajorIterationFrequency ()

int	getMajorIterationFrequency ()

boolean	hasTerminationCheckFrequency ()

int	getTerminationCheckFrequency ()

boolean	hasRestartStrategy ()

com.google.ortools.pdlp.PrimalDualHybridGradientParams.RestartStrategy	getRestartStrategy ()

boolean	hasPrimalWeightUpdateSmoothing ()

double	getPrimalWeightUpdateSmoothing ()

boolean	hasInitialPrimalWeight ()

double	getInitialPrimalWeight ()

boolean	hasPresolveOptions ()

com.google.ortools.pdlp.PrimalDualHybridGradientParams.PresolveOptions	getPresolveOptions ()

com.google.ortools.pdlp.PrimalDualHybridGradientParams.PresolveOptionsOrBuilder	getPresolveOptionsOrBuilder ()

boolean	hasLInfRuizIterations ()

int	getLInfRuizIterations ()

boolean	hasL2NormRescaling ()

boolean	getL2NormRescaling ()

boolean	hasSufficientReductionForRestart ()

double	getSufficientReductionForRestart ()

boolean	hasNecessaryReductionForRestart ()

double	getNecessaryReductionForRestart ()

boolean	hasLinesearchRule ()

com.google.ortools.pdlp.PrimalDualHybridGradientParams.LinesearchRule	getLinesearchRule ()

boolean	hasAdaptiveLinesearchParameters ()

com.google.ortools.pdlp.AdaptiveLinesearchParams	getAdaptiveLinesearchParameters ()

com.google.ortools.pdlp.AdaptiveLinesearchParamsOrBuilder	getAdaptiveLinesearchParametersOrBuilder ()

boolean	hasMalitskyPockParameters ()

com.google.ortools.pdlp.MalitskyPockParams	getMalitskyPockParameters ()

com.google.ortools.pdlp.MalitskyPockParamsOrBuilder	getMalitskyPockParametersOrBuilder ()

boolean	hasInitialStepSizeScaling ()

double	getInitialStepSizeScaling ()

java.util.List< java.lang.Integer >	getRandomProjectionSeedsList ()

int	getRandomProjectionSeedsCount ()

int	getRandomProjectionSeeds (int index)

boolean	hasInfiniteConstraintBoundThreshold ()

double	getInfiniteConstraintBoundThreshold ()

boolean	hasHandleSomePrimalGradientsOnFiniteBoundsAsResiduals ()

boolean	getHandleSomePrimalGradientsOnFiniteBoundsAsResiduals ()

boolean	hasUseDiagonalQpTrustRegionSolver ()

boolean	getUseDiagonalQpTrustRegionSolver ()

boolean	hasDiagonalQpTrustRegionSolverTolerance ()

double	getDiagonalQpTrustRegionSolverTolerance ()

boolean	hasUseFeasibilityPolishing ()

boolean	getUseFeasibilityPolishing ()

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< PrimalDualHybridGradientParams >	getParserForType ()

com.google.ortools.pdlp.PrimalDualHybridGradientParams	getDefaultInstanceForType ()

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

static com.google.ortools.pdlp.PrimalDualHybridGradientParams	parseFrom (java.nio.ByteBuffer data) throws com.google.protobuf.InvalidProtocolBufferException

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

static com.google.ortools.pdlp.PrimalDualHybridGradientParams	parseFrom (com.google.protobuf.ByteString data) throws com.google.protobuf.InvalidProtocolBufferException

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

static com.google.ortools.pdlp.PrimalDualHybridGradientParams	parseFrom (byte[] data) throws com.google.protobuf.InvalidProtocolBufferException

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

static com.google.ortools.pdlp.PrimalDualHybridGradientParams	parseFrom (java.io.InputStream input) throws java.io.IOException

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

static com.google.ortools.pdlp.PrimalDualHybridGradientParams	parseDelimitedFrom (java.io.InputStream input) throws java.io.IOException

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

static com.google.ortools.pdlp.PrimalDualHybridGradientParams	parseFrom (com.google.protobuf.CodedInputStream input) throws java.io.IOException

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

static Builder	newBuilder ()

static Builder	newBuilder (com.google.ortools.pdlp.PrimalDualHybridGradientParams prototype)

static com.google.ortools.pdlp.PrimalDualHybridGradientParams	getDefaultInstance ()

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

Static Public Attributes
static final int	TERMINATION_CRITERIA_FIELD_NUMBER = 1

static final int	NUM_THREADS_FIELD_NUMBER = 2

static final int	NUM_SHARDS_FIELD_NUMBER = 27

static final int	SCHEDULER_TYPE_FIELD_NUMBER = 32

static final int	RECORD_ITERATION_STATS_FIELD_NUMBER = 3

static final int	VERBOSITY_LEVEL_FIELD_NUMBER = 26

static final int	LOG_INTERVAL_SECONDS_FIELD_NUMBER = 31

static final int	MAJOR_ITERATION_FREQUENCY_FIELD_NUMBER = 4

static final int	TERMINATION_CHECK_FREQUENCY_FIELD_NUMBER = 5

static final int	RESTART_STRATEGY_FIELD_NUMBER = 6

static final int	PRIMAL_WEIGHT_UPDATE_SMOOTHING_FIELD_NUMBER = 7

static final int	INITIAL_PRIMAL_WEIGHT_FIELD_NUMBER = 8

static final int	PRESOLVE_OPTIONS_FIELD_NUMBER = 16

static final int	L_INF_RUIZ_ITERATIONS_FIELD_NUMBER = 9

static final int	L2_NORM_RESCALING_FIELD_NUMBER = 10

static final int	SUFFICIENT_REDUCTION_FOR_RESTART_FIELD_NUMBER = 11

static final int	NECESSARY_REDUCTION_FOR_RESTART_FIELD_NUMBER = 17

static final int	LINESEARCH_RULE_FIELD_NUMBER = 12

static final int	ADAPTIVE_LINESEARCH_PARAMETERS_FIELD_NUMBER = 18

static final int	MALITSKY_POCK_PARAMETERS_FIELD_NUMBER = 19

static final int	INITIAL_STEP_SIZE_SCALING_FIELD_NUMBER = 25

static final int	RANDOM_PROJECTION_SEEDS_FIELD_NUMBER = 28

static final int	INFINITE_CONSTRAINT_BOUND_THRESHOLD_FIELD_NUMBER = 22

static final int	HANDLE_SOME_PRIMAL_GRADIENTS_ON_FINITE_BOUNDS_AS_RESIDUALS_FIELD_NUMBER = 29

static final int	USE_DIAGONAL_QP_TRUST_REGION_SOLVER_FIELD_NUMBER = 23

static final int	DIAGONAL_QP_TRUST_REGION_SOLVER_TOLERANCE_FIELD_NUMBER = 24

static final int	USE_FEASIBILITY_POLISHING_FIELD_NUMBER = 30

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

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

Detailed Description

Parameters for PrimalDualHybridGradient() in primal_dual_hybrid_gradient.h.
While the defaults are generally good, it is usually worthwhile to perform a
parameter sweep to find good settings for a particular family of problems.
The following parameters should be considered for tuning:
- restart_strategy (jointly with major_iteration_frequency)
- primal_weight_update_smoothing (jointly with initial_primal_weight)
- presolve_options.use_glop
- l_inf_ruiz_iterations
- l2_norm_rescaling
In addition, tune num_threads to speed up the solve.

Protobuf type operations_research.pdlp.PrimalDualHybridGradientParams

Definition at line 24 of file PrimalDualHybridGradientParams.java.

Member Function Documentation

◆ equals()

boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.equals ( final java.lang.Object obj )

Definition at line 2444 of file PrimalDualHybridGradientParams.java.

◆ getAdaptiveLinesearchParameters()

com.google.ortools.pdlp.AdaptiveLinesearchParams com.google.ortools.pdlp.PrimalDualHybridGradientParams.getAdaptiveLinesearchParameters ( )

optional .operations_research.pdlp.AdaptiveLinesearchParams adaptive_linesearch_parameters = 18;

Returns: The adaptiveLinesearchParameters.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1871 of file PrimalDualHybridGradientParams.java.

◆ getAdaptiveLinesearchParametersOrBuilder()

com.google.ortools.pdlp.AdaptiveLinesearchParamsOrBuilder com.google.ortools.pdlp.PrimalDualHybridGradientParams.getAdaptiveLinesearchParametersOrBuilder ( )

optional .operations_research.pdlp.AdaptiveLinesearchParams adaptive_linesearch_parameters = 18;

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1878 of file PrimalDualHybridGradientParams.java.

◆ getDefaultInstance()

static com.google.ortools.pdlp.PrimalDualHybridGradientParams com.google.ortools.pdlp.PrimalDualHybridGradientParams.getDefaultInstance ( )

static

Definition at line 5676 of file PrimalDualHybridGradientParams.java.

◆ getDefaultInstanceForType()

com.google.ortools.pdlp.PrimalDualHybridGradientParams com.google.ortools.pdlp.PrimalDualHybridGradientParams.getDefaultInstanceForType ( )

Definition at line 5712 of file PrimalDualHybridGradientParams.java.

◆ getDescriptor()

static final com.google.protobuf.Descriptors.Descriptor com.google.ortools.pdlp.PrimalDualHybridGradientParams.getDescriptor ( )

static

Definition at line 62 of file PrimalDualHybridGradientParams.java.

◆ getDiagonalQpTrustRegionSolverTolerance()

double com.google.ortools.pdlp.PrimalDualHybridGradientParams.getDiagonalQpTrustRegionSolverTolerance ( )

The solve tolerance of the experimental trust region solver for diagonal
QPs, controlling the accuracy of binary search over a one-dimensional
scaling parameter. Smaller values imply smaller relative error of the final
solution vector.
TODO(user): Find an expression for the final relative error.

optional double diagonal_qp_trust_region_solver_tolerance = 24 [default = 1e-08];

Returns: The diagonalQpTrustRegionSolverTolerance.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 2130 of file PrimalDualHybridGradientParams.java.

◆ getHandleSomePrimalGradientsOnFiniteBoundsAsResiduals()

boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.getHandleSomePrimalGradientsOnFiniteBoundsAsResiduals ( )

See
https://developers.google.com/optimization/lp/pdlp_math#treating_some_variable_bounds_as_infinite
for a description of this flag.

optional bool handle_some_primal_gradients_on_finite_bounds_as_residuals = 29 [default = true];

Returns: The handleSomePrimalGradientsOnFiniteBoundsAsResiduals.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 2058 of file PrimalDualHybridGradientParams.java.

◆ getInfiniteConstraintBoundThreshold()

double com.google.ortools.pdlp.PrimalDualHybridGradientParams.getInfiniteConstraintBoundThreshold ( )

Constraint bounds with absolute value at least this threshold are replaced
with infinities.
NOTE: This primarily affects the relative convergence criteria. A smaller
value makes the relative convergence criteria stronger. It also affects the
problem statistics LOG()ed at the start of the run, and the default initial
primal weight, since that is based on the norm of the bounds.

optional double infinite_constraint_bound_threshold = 22 [default = inf];

Returns: The infiniteConstraintBoundThreshold.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 2027 of file PrimalDualHybridGradientParams.java.

◆ getInitialPrimalWeight()

double com.google.ortools.pdlp.PrimalDualHybridGradientParams.getInitialPrimalWeight ( )

The initial value of the primal weight (i.e., the ratio of primal and dual
step sizes). The primal weight remains fixed throughout the solve if
primal_weight_update_smoothing = 0.0. If unset, the default is the ratio of
the norm of the objective vector to the L2 norm of the combined constraint
bounds vector (as defined above). If this ratio is not finite and positive,
then the default is 1.0 instead. For tuning, try powers of 10, for example,
from 10^{-6} to 10^6.

optional double initial_primal_weight = 8;

Returns: The initialPrimalWeight.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1674 of file PrimalDualHybridGradientParams.java.

◆ getInitialStepSizeScaling()

double com.google.ortools.pdlp.PrimalDualHybridGradientParams.getInitialStepSizeScaling ( )

Scaling factor applied to the initial step size (all step sizes if
linesearch_rule == CONSTANT_STEP_SIZE_RULE).

optional double initial_step_size_scaling = 25 [default = 1];

Returns: The initialStepSizeScaling.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1933 of file PrimalDualHybridGradientParams.java.

◆ getL2NormRescaling()

boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.getL2NormRescaling ( )

If true, applies L_2 norm rescaling after the Ruiz rescaling. Heuristically
this has been found to help convergence.

optional bool l2_norm_rescaling = 10 [default = true];

Returns: The l2NormRescaling.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1760 of file PrimalDualHybridGradientParams.java.

◆ getLinesearchRule()

com.google.ortools.pdlp.PrimalDualHybridGradientParams.LinesearchRule com.google.ortools.pdlp.PrimalDualHybridGradientParams.getLinesearchRule ( )

Linesearch rule applied at each major iteration.

optional .operations_research.pdlp.PrimalDualHybridGradientParams.LinesearchRule linesearch_rule = 12 [default = ADAPTIVE_LINESEARCH_RULE];

Returns: The linesearchRule.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1851 of file PrimalDualHybridGradientParams.java.

◆ getLInfRuizIterations()

int com.google.ortools.pdlp.PrimalDualHybridGradientParams.getLInfRuizIterations ( )

Number of L_infinity Ruiz rescaling iterations to apply to the constraint
matrix. Zero disables this rescaling pass. Recommended values to try when
tuning are 0, 5, and 10.

optional int32 l_inf_ruiz_iterations = 9 [default = 5];

Returns: The lInfRuizIterations.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1731 of file PrimalDualHybridGradientParams.java.

◆ getLogIntervalSeconds()

double com.google.ortools.pdlp.PrimalDualHybridGradientParams.getLogIntervalSeconds ( )

Time between iteration-level statistics logging (if `verbosity_level > 1`).
Since iteration-level statistics are only generated when performing
termination checks, logs will be generated from next termination check
after `log_interval_seconds` have elapsed. Should be >= 0.0. 0.0 (the
default) means log statistics at every termination check.

optional double log_interval_seconds = 31 [default = 0];

Returns: The logIntervalSeconds.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1496 of file PrimalDualHybridGradientParams.java.

◆ getMajorIterationFrequency()

int com.google.ortools.pdlp.PrimalDualHybridGradientParams.getMajorIterationFrequency ( )

The frequency at which extra work is performed to make major algorithmic
decisions, e.g., performing restarts and updating the primal weight. Major
iterations also trigger a termination check. For best performance using the
NO_RESTARTS or EVERY_MAJOR_ITERATION rule, one should perform a log-scale
grid search over this parameter, for example, over powers of two.
ADAPTIVE_HEURISTIC is mostly insensitive to this value.

optional int32 major_iteration_frequency = 4 [default = 64];

Returns: The majorIterationFrequency.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1533 of file PrimalDualHybridGradientParams.java.

◆ getMalitskyPockParameters()

com.google.ortools.pdlp.MalitskyPockParams com.google.ortools.pdlp.PrimalDualHybridGradientParams.getMalitskyPockParameters ( )

optional .operations_research.pdlp.MalitskyPockParams malitsky_pock_parameters = 19;

Returns: The malitskyPockParameters.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1897 of file PrimalDualHybridGradientParams.java.

◆ getMalitskyPockParametersOrBuilder()

com.google.ortools.pdlp.MalitskyPockParamsOrBuilder com.google.ortools.pdlp.PrimalDualHybridGradientParams.getMalitskyPockParametersOrBuilder ( )

optional .operations_research.pdlp.MalitskyPockParams malitsky_pock_parameters = 19;

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1904 of file PrimalDualHybridGradientParams.java.

◆ getNecessaryReductionForRestart()

double com.google.ortools.pdlp.PrimalDualHybridGradientParams.getNecessaryReductionForRestart ( )

For ADAPTIVE_HEURISTIC only: A relative reduction in the potential function
by this amount triggers a restart if, additionally, the quality of the
iterates appears to be getting worse. The value must be in the interval
[sufficient_reduction_for_restart, 1). Smaller values make restarts less
frequent, and larger values make them more frequent.

optional double necessary_reduction_for_restart = 17 [default = 0.9];

Returns: The necessaryReductionForRestart.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1826 of file PrimalDualHybridGradientParams.java.

◆ getNumShards()

int com.google.ortools.pdlp.PrimalDualHybridGradientParams.getNumShards ( )

For more efficient parallel computation, the matrices and vectors are
divided (virtually) into num_shards shards. Results are computed
independently for each shard and then combined. As a consequence, the order
of computation, and hence floating point roundoff, depends on the number of
shards so reproducible results require using the same value for num_shards.
However, for efficiency num_shards should a be at least num_threads, and
preferably at least 4*num_threads to allow better load balancing. If
num_shards is positive, the computation will use that many shards.
Otherwise a default that depends on num_threads will be used.

optional int32 num_shards = 27 [default = 0];

Returns: The numShards.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1353 of file PrimalDualHybridGradientParams.java.

◆ getNumThreads()

int com.google.ortools.pdlp.PrimalDualHybridGradientParams.getNumThreads ( )

The number of threads to use. Must be positive.
Try various values of num_threads, up to the number of physical cores.
Performance may not be monotonically increasing with the number of threads
because of memory bandwidth limitations.

optional int32 num_threads = 2 [default = 1];

Returns: The numThreads.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1310 of file PrimalDualHybridGradientParams.java.

◆ getParserForType()

com.google.protobuf.Parser< PrimalDualHybridGradientParams > com.google.ortools.pdlp.PrimalDualHybridGradientParams.getParserForType ( )

Definition at line 5707 of file PrimalDualHybridGradientParams.java.

◆ getPresolveOptions()

com.google.ortools.pdlp.PrimalDualHybridGradientParams.PresolveOptions com.google.ortools.pdlp.PrimalDualHybridGradientParams.getPresolveOptions ( )

optional .operations_research.pdlp.PrimalDualHybridGradientParams.PresolveOptions presolve_options = 16;

Returns: The presolveOptions.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1693 of file PrimalDualHybridGradientParams.java.

◆ getPresolveOptionsOrBuilder()

com.google.ortools.pdlp.PrimalDualHybridGradientParams.PresolveOptionsOrBuilder com.google.ortools.pdlp.PrimalDualHybridGradientParams.getPresolveOptionsOrBuilder ( )

optional .operations_research.pdlp.PrimalDualHybridGradientParams.PresolveOptions presolve_options = 16;

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1700 of file PrimalDualHybridGradientParams.java.

◆ getPrimalWeightUpdateSmoothing()

double com.google.ortools.pdlp.PrimalDualHybridGradientParams.getPrimalWeightUpdateSmoothing ( )

This parameter controls exponential smoothing of log(primal_weight) when a
primal weight update occurs (i.e., when the ratio of primal and dual step
sizes is adjusted). At 0.0, the primal weight will be frozen at its initial
value and there will be no dynamic updates in the algorithm. At 1.0, there
is no smoothing in the updates. The default of 0.5 generally performs well,
but has been observed on occasion to trigger unstable swings in the primal
weight. We recommend also trying 0.0 (disabling primal weight updates), in
which case you must also tune initial_primal_weight.

optional double primal_weight_update_smoothing = 7 [default = 0.5];

Returns: The primalWeightUpdateSmoothing.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1635 of file PrimalDualHybridGradientParams.java.

◆ getRandomProjectionSeeds()

int com.google.ortools.pdlp.PrimalDualHybridGradientParams.getRandomProjectionSeeds ( int index )

Seeds for generating (pseudo-)random projections of iterates during
termination checks. For each seed, the projection of the primal and dual
solutions onto random planes in primal and dual space will be computed and
added the IterationStats if record_iteration_stats is true. The random
planes generated will be determined by the seeds, the primal and dual
dimensions, and num_threads.

repeated int32 random_projection_seeds = 28 [packed = true];

Parameters

index The index of the element to return.

Returns: The randomProjectionSeeds at the given index.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1989 of file PrimalDualHybridGradientParams.java.

◆ getRandomProjectionSeedsCount()

int com.google.ortools.pdlp.PrimalDualHybridGradientParams.getRandomProjectionSeedsCount ( )

Seeds for generating (pseudo-)random projections of iterates during
termination checks. For each seed, the projection of the primal and dual
solutions onto random planes in primal and dual space will be computed and
added the IterationStats if record_iteration_stats is true. The random
planes generated will be determined by the seeds, the primal and dual
dimensions, and num_threads.

repeated int32 random_projection_seeds = 28 [packed = true];

Returns: The count of randomProjectionSeeds.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1972 of file PrimalDualHybridGradientParams.java.

◆ getRandomProjectionSeedsList()

java.util.List< java.lang.Integer > com.google.ortools.pdlp.PrimalDualHybridGradientParams.getRandomProjectionSeedsList ( )

Seeds for generating (pseudo-)random projections of iterates during
termination checks. For each seed, the projection of the primal and dual
solutions onto random planes in primal and dual space will be computed and
added the IterationStats if record_iteration_stats is true. The random
planes generated will be determined by the seeds, the primal and dual
dimensions, and num_threads.

repeated int32 random_projection_seeds = 28 [packed = true];

Returns: A list containing the randomProjectionSeeds.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1956 of file PrimalDualHybridGradientParams.java.

◆ getRecordIterationStats()

boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.getRecordIterationStats ( )

If true, the iteration_stats field of the SolveLog output will be populated
at every iteration. Note that we only compute solution statistics at
termination checks. Setting this parameter to true may substantially
increase the size of the output.

optional bool record_iteration_stats = 3;

Returns: The recordIterationStats.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1414 of file PrimalDualHybridGradientParams.java.

◆ getRestartStrategy()

com.google.ortools.pdlp.PrimalDualHybridGradientParams.RestartStrategy com.google.ortools.pdlp.PrimalDualHybridGradientParams.getRestartStrategy ( )

NO_RESTARTS and EVERY_MAJOR_ITERATION occasionally outperform the default.
If using a strategy other than ADAPTIVE_HEURISTIC, you must also tune
major_iteration_frequency.

optional .operations_research.pdlp.PrimalDualHybridGradientParams.RestartStrategy restart_strategy = 6 [default = ADAPTIVE_HEURISTIC];

Returns: The restartStrategy.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1593 of file PrimalDualHybridGradientParams.java.

◆ getSchedulerType()

com.google.ortools.pdlp.SchedulerType com.google.ortools.pdlp.PrimalDualHybridGradientParams.getSchedulerType ( )

The type of scheduler used for CPU multi-threading. See the documentation
of the corresponding enum for more details.

optional .operations_research.pdlp.SchedulerType scheduler_type = 32 [default = SCHEDULER_TYPE_GOOGLE_THREADPOOL];

Returns: The schedulerType.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1380 of file PrimalDualHybridGradientParams.java.

◆ getSerializedSize()

int com.google.ortools.pdlp.PrimalDualHybridGradientParams.getSerializedSize ( )

Definition at line 2315 of file PrimalDualHybridGradientParams.java.

◆ getSufficientReductionForRestart()

double com.google.ortools.pdlp.PrimalDualHybridGradientParams.getSufficientReductionForRestart ( )

For ADAPTIVE_HEURISTIC and ADAPTIVE_DISTANCE_BASED only: A relative
reduction in the potential function by this amount always triggers a
restart. Must be between 0.0 and 1.0.

optional double sufficient_reduction_for_restart = 11 [default = 0.1];

Returns: The sufficientReductionForRestart.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1791 of file PrimalDualHybridGradientParams.java.

◆ getTerminationCheckFrequency()

int com.google.ortools.pdlp.PrimalDualHybridGradientParams.getTerminationCheckFrequency ( )

The frequency (based on a counter reset every major iteration) to check for
termination (involves extra work) and log iteration stats. Termination
checks do not affect algorithmic progress unless termination is triggered.

optional int32 termination_check_frequency = 5 [default = 64];

Returns: The terminationCheckFrequency.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1564 of file PrimalDualHybridGradientParams.java.

◆ getTerminationCriteria()

com.google.ortools.pdlp.TerminationCriteria com.google.ortools.pdlp.PrimalDualHybridGradientParams.getTerminationCriteria ( )

optional .operations_research.pdlp.TerminationCriteria termination_criteria = 1;

Returns: The terminationCriteria.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1270 of file PrimalDualHybridGradientParams.java.

◆ getTerminationCriteriaOrBuilder()

com.google.ortools.pdlp.TerminationCriteriaOrBuilder com.google.ortools.pdlp.PrimalDualHybridGradientParams.getTerminationCriteriaOrBuilder ( )

optional .operations_research.pdlp.TerminationCriteria termination_criteria = 1;

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1277 of file PrimalDualHybridGradientParams.java.

◆ getUseDiagonalQpTrustRegionSolver()

boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.getUseDiagonalQpTrustRegionSolver ( )

When solving QPs with diagonal objective matrices, this option can be
turned on to enable an experimental solver that avoids linearization of the
quadratic term. The `diagonal_qp_solver_accuracy` parameter controls the
solve accuracy.
TODO(user): Turn this option on by default for quadratic
programs after numerical evaluation.

optional bool use_diagonal_qp_trust_region_solver = 23 [default = false];

Returns: The useDiagonalQpTrustRegionSolver.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 2095 of file PrimalDualHybridGradientParams.java.

◆ getUseFeasibilityPolishing()

boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.getUseFeasibilityPolishing ( )

If true, periodically runs feasibility polishing, which attempts to move
from latest average iterate to one that is closer to feasibility (i.e., has
smaller primal and dual residuals) while probably increasing the objective
gap. This is useful primarily when the feasibility tolerances are fairly
tight and the objective gap tolerance is somewhat looser. Note that this
does not change the termination criteria, but rather can help achieve the
termination criteria more quickly when the objective gap is not as
important as feasibility.

`use_feasibility_polishing` cannot be used with glop presolve, and requires
`handle_some_primal_gradients_on_finite_bounds_as_residuals == false`.
`use_feasibility_polishing` can only be used with linear programs.

Feasibility polishing runs two separate phases, primal feasibility and dual
feasibility. The primal feasibility phase runs PDHG on the primal
feasibility problem (obtained by changing the objective vector to all
zeros), using the average primal iterate and zero dual (which is optimal
for the primal feasibility problem) as the initial solution. The dual
feasibility phase runs PDHG on the dual feasibility problem (obtained by
changing all finite variable and constraint bounds to zero), using the
average dual iterate and zero primal (which is optimal for the dual
feasibility problem) as the initial solution. The primal solution from the
primal feasibility phase and dual solution from the dual feasibility phase
are then combined (forming a solution of type
`POINT_TYPE_FEASIBILITY_POLISHING_SOLUTION`) and checked against the
termination criteria.

optional bool use_feasibility_polishing = 30 [default = false];

Returns: The useFeasibilityPolishing.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 2207 of file PrimalDualHybridGradientParams.java.

◆ getVerbosityLevel()

int com.google.ortools.pdlp.PrimalDualHybridGradientParams.getVerbosityLevel ( )

The verbosity of logging.
0: No informational logging. (Errors are logged.)
1: Summary statistics only. No iteration-level details.
2: A table of iteration-level statistics is logged.
(See ToShortString() in primal_dual_hybrid_gradient.cc).
3: A more detailed table of iteration-level statistics is logged.
(See ToString() in primal_dual_hybrid_gradient.cc).
4: For iteration-level details, prints the statistics of both the average
(prefixed with A) and the current iterate (prefixed with C). Also prints
internal algorithmic state and details.
Logging at levels 2-4 also includes messages from level 1.

optional int32 verbosity_level = 26 [default = 0];

Returns: The verbosityLevel.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1461 of file PrimalDualHybridGradientParams.java.

◆ hasAdaptiveLinesearchParameters()

boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasAdaptiveLinesearchParameters ( )

optional .operations_research.pdlp.AdaptiveLinesearchParams adaptive_linesearch_parameters = 18;

Returns: Whether the adaptiveLinesearchParameters field is set.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1863 of file PrimalDualHybridGradientParams.java.

◆ hasDiagonalQpTrustRegionSolverTolerance()

boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasDiagonalQpTrustRegionSolverTolerance ( )

The solve tolerance of the experimental trust region solver for diagonal
QPs, controlling the accuracy of binary search over a one-dimensional
scaling parameter. Smaller values imply smaller relative error of the final
solution vector.
TODO(user): Find an expression for the final relative error.

optional double diagonal_qp_trust_region_solver_tolerance = 24 [default = 1e-08];

Returns: Whether the diagonalQpTrustRegionSolverTolerance field is set.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 2114 of file PrimalDualHybridGradientParams.java.

◆ hasHandleSomePrimalGradientsOnFiniteBoundsAsResiduals()

boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasHandleSomePrimalGradientsOnFiniteBoundsAsResiduals ( )

See
https://developers.google.com/optimization/lp/pdlp_math#treating_some_variable_bounds_as_infinite
for a description of this flag.

optional bool handle_some_primal_gradients_on_finite_bounds_as_residuals = 29 [default = true];

Returns: Whether the handleSomePrimalGradientsOnFiniteBoundsAsResiduals field is set.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 2044 of file PrimalDualHybridGradientParams.java.

◆ hashCode()

int com.google.ortools.pdlp.PrimalDualHybridGradientParams.hashCode ( )

Definition at line 2595 of file PrimalDualHybridGradientParams.java.

◆ hasInfiniteConstraintBoundThreshold()

boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasInfiniteConstraintBoundThreshold ( )

Constraint bounds with absolute value at least this threshold are replaced
with infinities.
NOTE: This primarily affects the relative convergence criteria. A smaller
value makes the relative convergence criteria stronger. It also affects the
problem statistics LOG()ed at the start of the run, and the default initial
primal weight, since that is based on the norm of the bounds.

optional double infinite_constraint_bound_threshold = 22 [default = inf];

Returns: Whether the infiniteConstraintBoundThreshold field is set.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 2010 of file PrimalDualHybridGradientParams.java.

◆ hasInitialPrimalWeight()

boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasInitialPrimalWeight ( )

The initial value of the primal weight (i.e., the ratio of primal and dual
step sizes). The primal weight remains fixed throughout the solve if
primal_weight_update_smoothing = 0.0. If unset, the default is the ratio of
the norm of the objective vector to the L2 norm of the combined constraint
bounds vector (as defined above). If this ratio is not finite and positive,
then the default is 1.0 instead. For tuning, try powers of 10, for example,
from 10^{-6} to 10^6.

optional double initial_primal_weight = 8;

Returns: Whether the initialPrimalWeight field is set.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1656 of file PrimalDualHybridGradientParams.java.

◆ hasInitialStepSizeScaling()

boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasInitialStepSizeScaling ( )

Scaling factor applied to the initial step size (all step sizes if
linesearch_rule == CONSTANT_STEP_SIZE_RULE).

optional double initial_step_size_scaling = 25 [default = 1];

Returns: Whether the initialStepSizeScaling field is set.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1920 of file PrimalDualHybridGradientParams.java.

◆ hasL2NormRescaling()

boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasL2NormRescaling ( )

If true, applies L_2 norm rescaling after the Ruiz rescaling. Heuristically
this has been found to help convergence.

optional bool l2_norm_rescaling = 10 [default = true];

Returns: Whether the l2NormRescaling field is set.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1747 of file PrimalDualHybridGradientParams.java.

◆ hasLinesearchRule()

boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasLinesearchRule ( )

Linesearch rule applied at each major iteration.

optional .operations_research.pdlp.PrimalDualHybridGradientParams.LinesearchRule linesearch_rule = 12 [default = ADAPTIVE_LINESEARCH_RULE];

Returns: Whether the linesearchRule field is set.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1840 of file PrimalDualHybridGradientParams.java.

◆ hasLInfRuizIterations()

boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasLInfRuizIterations ( )

Number of L_infinity Ruiz rescaling iterations to apply to the constraint
matrix. Zero disables this rescaling pass. Recommended values to try when
tuning are 0, 5, and 10.

optional int32 l_inf_ruiz_iterations = 9 [default = 5];

Returns: Whether the lInfRuizIterations field is set.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1717 of file PrimalDualHybridGradientParams.java.

◆ hasLogIntervalSeconds()

boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasLogIntervalSeconds ( )

Time between iteration-level statistics logging (if `verbosity_level > 1`).
Since iteration-level statistics are only generated when performing
termination checks, logs will be generated from next termination check
after `log_interval_seconds` have elapsed. Should be >= 0.0. 0.0 (the
default) means log statistics at every termination check.

optional double log_interval_seconds = 31 [default = 0];

Returns: Whether the logIntervalSeconds field is set.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1480 of file PrimalDualHybridGradientParams.java.

◆ hasMajorIterationFrequency()

boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasMajorIterationFrequency ( )

The frequency at which extra work is performed to make major algorithmic
decisions, e.g., performing restarts and updating the primal weight. Major
iterations also trigger a termination check. For best performance using the
NO_RESTARTS or EVERY_MAJOR_ITERATION rule, one should perform a log-scale
grid search over this parameter, for example, over powers of two.
ADAPTIVE_HEURISTIC is mostly insensitive to this value.

optional int32 major_iteration_frequency = 4 [default = 64];

Returns: Whether the majorIterationFrequency field is set.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1516 of file PrimalDualHybridGradientParams.java.

◆ hasMalitskyPockParameters()

boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasMalitskyPockParameters ( )

optional .operations_research.pdlp.MalitskyPockParams malitsky_pock_parameters = 19;

Returns: Whether the malitskyPockParameters field is set.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1889 of file PrimalDualHybridGradientParams.java.

◆ hasNecessaryReductionForRestart()

boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasNecessaryReductionForRestart ( )

For ADAPTIVE_HEURISTIC only: A relative reduction in the potential function
by this amount triggers a restart if, additionally, the quality of the
iterates appears to be getting worse. The value must be in the interval
[sufficient_reduction_for_restart, 1). Smaller values make restarts less
frequent, and larger values make them more frequent.

optional double necessary_reduction_for_restart = 17 [default = 0.9];

Returns: Whether the necessaryReductionForRestart field is set.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1810 of file PrimalDualHybridGradientParams.java.

◆ hasNumShards()

boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasNumShards ( )

For more efficient parallel computation, the matrices and vectors are
divided (virtually) into num_shards shards. Results are computed
independently for each shard and then combined. As a consequence, the order
of computation, and hence floating point roundoff, depends on the number of
shards so reproducible results require using the same value for num_shards.
However, for efficiency num_shards should a be at least num_threads, and
preferably at least 4*num_threads to allow better load balancing. If
num_shards is positive, the computation will use that many shards.
Otherwise a default that depends on num_threads will be used.

optional int32 num_shards = 27 [default = 0];

Returns: Whether the numShards field is set.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1333 of file PrimalDualHybridGradientParams.java.

◆ hasNumThreads()

boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasNumThreads ( )

The number of threads to use. Must be positive.
Try various values of num_threads, up to the number of physical cores.
Performance may not be monotonically increasing with the number of threads
because of memory bandwidth limitations.

optional int32 num_threads = 2 [default = 1];

Returns: Whether the numThreads field is set.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1295 of file PrimalDualHybridGradientParams.java.

◆ hasPresolveOptions()

boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasPresolveOptions ( )

optional .operations_research.pdlp.PrimalDualHybridGradientParams.PresolveOptions presolve_options = 16;

Returns: Whether the presolveOptions field is set.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1685 of file PrimalDualHybridGradientParams.java.

◆ hasPrimalWeightUpdateSmoothing()

boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasPrimalWeightUpdateSmoothing ( )

This parameter controls exponential smoothing of log(primal_weight) when a
primal weight update occurs (i.e., when the ratio of primal and dual step
sizes is adjusted). At 0.0, the primal weight will be frozen at its initial
value and there will be no dynamic updates in the algorithm. At 1.0, there
is no smoothing in the updates. The default of 0.5 generally performs well,
but has been observed on occasion to trigger unstable swings in the primal
weight. We recommend also trying 0.0 (disabling primal weight updates), in
which case you must also tune initial_primal_weight.

optional double primal_weight_update_smoothing = 7 [default = 0.5];

Returns: Whether the primalWeightUpdateSmoothing field is set.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1616 of file PrimalDualHybridGradientParams.java.

◆ hasRecordIterationStats()

boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasRecordIterationStats ( )

If true, the iteration_stats field of the SolveLog output will be populated
at every iteration. Note that we only compute solution statistics at
termination checks. Setting this parameter to true may substantially
increase the size of the output.

optional bool record_iteration_stats = 3;

Returns: Whether the recordIterationStats field is set.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1399 of file PrimalDualHybridGradientParams.java.

◆ hasRestartStrategy()

boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasRestartStrategy ( )

NO_RESTARTS and EVERY_MAJOR_ITERATION occasionally outperform the default.
If using a strategy other than ADAPTIVE_HEURISTIC, you must also tune
major_iteration_frequency.

optional .operations_research.pdlp.PrimalDualHybridGradientParams.RestartStrategy restart_strategy = 6 [default = ADAPTIVE_HEURISTIC];

Returns: Whether the restartStrategy field is set.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1580 of file PrimalDualHybridGradientParams.java.

◆ hasSchedulerType()

boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasSchedulerType ( )

The type of scheduler used for CPU multi-threading. See the documentation
of the corresponding enum for more details.

optional .operations_research.pdlp.SchedulerType scheduler_type = 32 [default = SCHEDULER_TYPE_GOOGLE_THREADPOOL];

Returns: Whether the schedulerType field is set.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1368 of file PrimalDualHybridGradientParams.java.

◆ hasSufficientReductionForRestart()

boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasSufficientReductionForRestart ( )

For ADAPTIVE_HEURISTIC and ADAPTIVE_DISTANCE_BASED only: A relative
reduction in the potential function by this amount always triggers a
restart. Must be between 0.0 and 1.0.

optional double sufficient_reduction_for_restart = 11 [default = 0.1];

Returns: Whether the sufficientReductionForRestart field is set.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1777 of file PrimalDualHybridGradientParams.java.

◆ hasTerminationCheckFrequency()

boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasTerminationCheckFrequency ( )

The frequency (based on a counter reset every major iteration) to check for
termination (involves extra work) and log iteration stats. Termination
checks do not affect algorithmic progress unless termination is triggered.

optional int32 termination_check_frequency = 5 [default = 64];

Returns: Whether the terminationCheckFrequency field is set.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1550 of file PrimalDualHybridGradientParams.java.

◆ hasTerminationCriteria()

boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasTerminationCriteria ( )

optional .operations_research.pdlp.TerminationCriteria termination_criteria = 1;

Returns: Whether the terminationCriteria field is set.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1262 of file PrimalDualHybridGradientParams.java.

◆ hasUseDiagonalQpTrustRegionSolver()

boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasUseDiagonalQpTrustRegionSolver ( )

When solving QPs with diagonal objective matrices, this option can be
turned on to enable an experimental solver that avoids linearization of the
quadratic term. The `diagonal_qp_solver_accuracy` parameter controls the
solve accuracy.
TODO(user): Turn this option on by default for quadratic
programs after numerical evaluation.

optional bool use_diagonal_qp_trust_region_solver = 23 [default = false];

Returns: Whether the useDiagonalQpTrustRegionSolver field is set.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 2078 of file PrimalDualHybridGradientParams.java.

◆ hasUseFeasibilityPolishing()

boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasUseFeasibilityPolishing ( )

If true, periodically runs feasibility polishing, which attempts to move
from latest average iterate to one that is closer to feasibility (i.e., has
smaller primal and dual residuals) while probably increasing the objective
gap. This is useful primarily when the feasibility tolerances are fairly
tight and the objective gap tolerance is somewhat looser. Note that this
does not change the termination criteria, but rather can help achieve the
termination criteria more quickly when the objective gap is not as
important as feasibility.

`use_feasibility_polishing` cannot be used with glop presolve, and requires
`handle_some_primal_gradients_on_finite_bounds_as_residuals == false`.
`use_feasibility_polishing` can only be used with linear programs.

Feasibility polishing runs two separate phases, primal feasibility and dual
feasibility. The primal feasibility phase runs PDHG on the primal
feasibility problem (obtained by changing the objective vector to all
zeros), using the average primal iterate and zero dual (which is optimal
for the primal feasibility problem) as the initial solution. The dual
feasibility phase runs PDHG on the dual feasibility problem (obtained by
changing all finite variable and constraint bounds to zero), using the
average dual iterate and zero primal (which is optimal for the dual
feasibility problem) as the initial solution. The primal solution from the
primal feasibility phase and dual solution from the dual feasibility phase
are then combined (forming a solution of type
`POINT_TYPE_FEASIBILITY_POLISHING_SOLUTION`) and checked against the
termination criteria.

optional bool use_feasibility_polishing = 30 [default = false];

Returns: Whether the useFeasibilityPolishing field is set.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 2170 of file PrimalDualHybridGradientParams.java.

◆ hasVerbosityLevel()

boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.hasVerbosityLevel ( )

The verbosity of logging.
0: No informational logging. (Errors are logged.)
1: Summary statistics only. No iteration-level details.
2: A table of iteration-level statistics is logged.
(See ToShortString() in primal_dual_hybrid_gradient.cc).
3: A more detailed table of iteration-level statistics is logged.
(See ToString() in primal_dual_hybrid_gradient.cc).
4: For iteration-level details, prints the statistics of both the average
(prefixed with A) and the current iterate (prefixed with C). Also prints
internal algorithmic state and details.
Logging at levels 2-4 also includes messages from level 1.

optional int32 verbosity_level = 26 [default = 0];

Returns: Whether the verbosityLevel field is set.

Implements com.google.ortools.pdlp.PrimalDualHybridGradientParamsOrBuilder.

Definition at line 1439 of file PrimalDualHybridGradientParams.java.

◆ internalGetFieldAccessorTable()

com.google.protobuf.GeneratedMessage.FieldAccessorTable com.google.ortools.pdlp.PrimalDualHybridGradientParams.internalGetFieldAccessorTable ( )

protected

Definition at line 68 of file PrimalDualHybridGradientParams.java.

◆ isInitialized()

final boolean com.google.ortools.pdlp.PrimalDualHybridGradientParams.isInitialized ( )

Definition at line 2213 of file PrimalDualHybridGradientParams.java.

◆ newBuilder() [1/2]

static Builder com.google.ortools.pdlp.PrimalDualHybridGradientParams.newBuilder ( )

static

Definition at line 2801 of file PrimalDualHybridGradientParams.java.

◆ newBuilder() [2/2]

static Builder com.google.ortools.pdlp.PrimalDualHybridGradientParams.newBuilder ( com.google.ortools.pdlp.PrimalDualHybridGradientParams prototype )

static

Definition at line 2804 of file PrimalDualHybridGradientParams.java.

◆ newBuilderForType() [1/2]

Builder com.google.ortools.pdlp.PrimalDualHybridGradientParams.newBuilderForType ( )

Definition at line 2800 of file PrimalDualHybridGradientParams.java.

◆ newBuilderForType() [2/2]

Builder com.google.ortools.pdlp.PrimalDualHybridGradientParams.newBuilderForType ( com.google.protobuf.GeneratedMessage.BuilderParent parent )

protected

Definition at line 2814 of file PrimalDualHybridGradientParams.java.

◆ parseDelimitedFrom() [1/2]

static com.google.ortools.pdlp.PrimalDualHybridGradientParams com.google.ortools.pdlp.PrimalDualHybridGradientParams.parseDelimitedFrom ( java.io.InputStream input ) throws java.io.IOException

static

Definition at line 2772 of file PrimalDualHybridGradientParams.java.

◆ parseDelimitedFrom() [2/2]

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

static

Definition at line 2778 of file PrimalDualHybridGradientParams.java.

◆ parseFrom() [1/10]

static com.google.ortools.pdlp.PrimalDualHybridGradientParams com.google.ortools.pdlp.PrimalDualHybridGradientParams.parseFrom ( byte[] data ) throws com.google.protobuf.InvalidProtocolBufferException

static

Definition at line 2749 of file PrimalDualHybridGradientParams.java.

◆ parseFrom() [2/10]

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

static

Definition at line 2753 of file PrimalDualHybridGradientParams.java.

◆ parseFrom() [3/10]

static com.google.ortools.pdlp.PrimalDualHybridGradientParams com.google.ortools.pdlp.PrimalDualHybridGradientParams.parseFrom ( com.google.protobuf.ByteString data ) throws com.google.protobuf.InvalidProtocolBufferException

static

Definition at line 2738 of file PrimalDualHybridGradientParams.java.

◆ parseFrom() [4/10]

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

static

Definition at line 2743 of file PrimalDualHybridGradientParams.java.

◆ parseFrom() [5/10]

static com.google.ortools.pdlp.PrimalDualHybridGradientParams com.google.ortools.pdlp.PrimalDualHybridGradientParams.parseFrom ( com.google.protobuf.CodedInputStream input ) throws java.io.IOException

static

Definition at line 2785 of file PrimalDualHybridGradientParams.java.

◆ parseFrom() [6/10]

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

static

Definition at line 2791 of file PrimalDualHybridGradientParams.java.

◆ parseFrom() [7/10]

static com.google.ortools.pdlp.PrimalDualHybridGradientParams com.google.ortools.pdlp.PrimalDualHybridGradientParams.parseFrom ( java.io.InputStream input ) throws java.io.IOException

static

Definition at line 2759 of file PrimalDualHybridGradientParams.java.

◆ parseFrom() [8/10]

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

static

Definition at line 2764 of file PrimalDualHybridGradientParams.java.

◆ parseFrom() [9/10]

static com.google.ortools.pdlp.PrimalDualHybridGradientParams com.google.ortools.pdlp.PrimalDualHybridGradientParams.parseFrom ( java.nio.ByteBuffer data ) throws com.google.protobuf.InvalidProtocolBufferException

static

Definition at line 2727 of file PrimalDualHybridGradientParams.java.

◆ parseFrom() [10/10]

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

static

Definition at line 2732 of file PrimalDualHybridGradientParams.java.

◆ parser()

static com.google.protobuf.Parser< PrimalDualHybridGradientParams > com.google.ortools.pdlp.PrimalDualHybridGradientParams.parser ( )

static

Definition at line 5702 of file PrimalDualHybridGradientParams.java.

◆ toBuilder()

Builder com.google.ortools.pdlp.PrimalDualHybridGradientParams.toBuilder ( )

Definition at line 2808 of file PrimalDualHybridGradientParams.java.

◆ writeTo()

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

Definition at line 2223 of file PrimalDualHybridGradientParams.java.

Member Data Documentation

◆ ADAPTIVE_LINESEARCH_PARAMETERS_FIELD_NUMBER

final int com.google.ortools.pdlp.PrimalDualHybridGradientParams.ADAPTIVE_LINESEARCH_PARAMETERS_FIELD_NUMBER = 18

static

Definition at line 1856 of file PrimalDualHybridGradientParams.java.

◆ DIAGONAL_QP_TRUST_REGION_SOLVER_TOLERANCE_FIELD_NUMBER

final int com.google.ortools.pdlp.PrimalDualHybridGradientParams.DIAGONAL_QP_TRUST_REGION_SOLVER_TOLERANCE_FIELD_NUMBER = 24

static

Definition at line 2099 of file PrimalDualHybridGradientParams.java.

◆ HANDLE_SOME_PRIMAL_GRADIENTS_ON_FINITE_BOUNDS_AS_RESIDUALS_FIELD_NUMBER

final int com.google.ortools.pdlp.PrimalDualHybridGradientParams.HANDLE_SOME_PRIMAL_GRADIENTS_ON_FINITE_BOUNDS_AS_RESIDUALS_FIELD_NUMBER = 29

static

Definition at line 2031 of file PrimalDualHybridGradientParams.java.

◆ INFINITE_CONSTRAINT_BOUND_THRESHOLD_FIELD_NUMBER

final int com.google.ortools.pdlp.PrimalDualHybridGradientParams.INFINITE_CONSTRAINT_BOUND_THRESHOLD_FIELD_NUMBER = 22

static

Definition at line 1994 of file PrimalDualHybridGradientParams.java.

◆ INITIAL_PRIMAL_WEIGHT_FIELD_NUMBER

final int com.google.ortools.pdlp.PrimalDualHybridGradientParams.INITIAL_PRIMAL_WEIGHT_FIELD_NUMBER = 8

static

Definition at line 1639 of file PrimalDualHybridGradientParams.java.

◆ INITIAL_STEP_SIZE_SCALING_FIELD_NUMBER

final int com.google.ortools.pdlp.PrimalDualHybridGradientParams.INITIAL_STEP_SIZE_SCALING_FIELD_NUMBER = 25

static

Definition at line 1908 of file PrimalDualHybridGradientParams.java.

◆ L2_NORM_RESCALING_FIELD_NUMBER

final int com.google.ortools.pdlp.PrimalDualHybridGradientParams.L2_NORM_RESCALING_FIELD_NUMBER = 10

static

Definition at line 1735 of file PrimalDualHybridGradientParams.java.

◆ L_INF_RUIZ_ITERATIONS_FIELD_NUMBER

final int com.google.ortools.pdlp.PrimalDualHybridGradientParams.L_INF_RUIZ_ITERATIONS_FIELD_NUMBER = 9

static

Definition at line 1704 of file PrimalDualHybridGradientParams.java.

◆ LINESEARCH_RULE_FIELD_NUMBER

final int com.google.ortools.pdlp.PrimalDualHybridGradientParams.LINESEARCH_RULE_FIELD_NUMBER = 12

static

Definition at line 1830 of file PrimalDualHybridGradientParams.java.

◆ LOG_INTERVAL_SECONDS_FIELD_NUMBER

final int com.google.ortools.pdlp.PrimalDualHybridGradientParams.LOG_INTERVAL_SECONDS_FIELD_NUMBER = 31

static

Definition at line 1465 of file PrimalDualHybridGradientParams.java.

◆ MAJOR_ITERATION_FREQUENCY_FIELD_NUMBER

final int com.google.ortools.pdlp.PrimalDualHybridGradientParams.MAJOR_ITERATION_FREQUENCY_FIELD_NUMBER = 4

static

Definition at line 1500 of file PrimalDualHybridGradientParams.java.

◆ MALITSKY_POCK_PARAMETERS_FIELD_NUMBER

final int com.google.ortools.pdlp.PrimalDualHybridGradientParams.MALITSKY_POCK_PARAMETERS_FIELD_NUMBER = 19

static

Definition at line 1882 of file PrimalDualHybridGradientParams.java.

◆ NECESSARY_REDUCTION_FOR_RESTART_FIELD_NUMBER

final int com.google.ortools.pdlp.PrimalDualHybridGradientParams.NECESSARY_REDUCTION_FOR_RESTART_FIELD_NUMBER = 17

static

Definition at line 1795 of file PrimalDualHybridGradientParams.java.

◆ NUM_SHARDS_FIELD_NUMBER

final int com.google.ortools.pdlp.PrimalDualHybridGradientParams.NUM_SHARDS_FIELD_NUMBER = 27

static

Definition at line 1314 of file PrimalDualHybridGradientParams.java.

◆ NUM_THREADS_FIELD_NUMBER

final int com.google.ortools.pdlp.PrimalDualHybridGradientParams.NUM_THREADS_FIELD_NUMBER = 2

static

Definition at line 1281 of file PrimalDualHybridGradientParams.java.

◆ PRESOLVE_OPTIONS_FIELD_NUMBER

final int com.google.ortools.pdlp.PrimalDualHybridGradientParams.PRESOLVE_OPTIONS_FIELD_NUMBER = 16

static

Definition at line 1678 of file PrimalDualHybridGradientParams.java.

◆ PRIMAL_WEIGHT_UPDATE_SMOOTHING_FIELD_NUMBER

final int com.google.ortools.pdlp.PrimalDualHybridGradientParams.PRIMAL_WEIGHT_UPDATE_SMOOTHING_FIELD_NUMBER = 7

static

Definition at line 1598 of file PrimalDualHybridGradientParams.java.

◆ RANDOM_PROJECTION_SEEDS_FIELD_NUMBER

final int com.google.ortools.pdlp.PrimalDualHybridGradientParams.RANDOM_PROJECTION_SEEDS_FIELD_NUMBER = 28

static

Definition at line 1937 of file PrimalDualHybridGradientParams.java.

◆ RECORD_ITERATION_STATS_FIELD_NUMBER

final int com.google.ortools.pdlp.PrimalDualHybridGradientParams.RECORD_ITERATION_STATS_FIELD_NUMBER = 3

static

Definition at line 1385 of file PrimalDualHybridGradientParams.java.

◆ RESTART_STRATEGY_FIELD_NUMBER

final int com.google.ortools.pdlp.PrimalDualHybridGradientParams.RESTART_STRATEGY_FIELD_NUMBER = 6

static

Definition at line 1568 of file PrimalDualHybridGradientParams.java.

◆ SCHEDULER_TYPE_FIELD_NUMBER

final int com.google.ortools.pdlp.PrimalDualHybridGradientParams.SCHEDULER_TYPE_FIELD_NUMBER = 32

static

Definition at line 1357 of file PrimalDualHybridGradientParams.java.

◆ SUFFICIENT_REDUCTION_FOR_RESTART_FIELD_NUMBER

final int com.google.ortools.pdlp.PrimalDualHybridGradientParams.SUFFICIENT_REDUCTION_FOR_RESTART_FIELD_NUMBER = 11

static

Definition at line 1764 of file PrimalDualHybridGradientParams.java.

◆ TERMINATION_CHECK_FREQUENCY_FIELD_NUMBER

final int com.google.ortools.pdlp.PrimalDualHybridGradientParams.TERMINATION_CHECK_FREQUENCY_FIELD_NUMBER = 5

static

Definition at line 1537 of file PrimalDualHybridGradientParams.java.

◆ TERMINATION_CRITERIA_FIELD_NUMBER

final int com.google.ortools.pdlp.PrimalDualHybridGradientParams.TERMINATION_CRITERIA_FIELD_NUMBER = 1

static

Definition at line 1255 of file PrimalDualHybridGradientParams.java.

◆ USE_DIAGONAL_QP_TRUST_REGION_SOLVER_FIELD_NUMBER

final int com.google.ortools.pdlp.PrimalDualHybridGradientParams.USE_DIAGONAL_QP_TRUST_REGION_SOLVER_FIELD_NUMBER = 23

static

Definition at line 2062 of file PrimalDualHybridGradientParams.java.

◆ USE_FEASIBILITY_POLISHING_FIELD_NUMBER

final int com.google.ortools.pdlp.PrimalDualHybridGradientParams.USE_FEASIBILITY_POLISHING_FIELD_NUMBER = 30

static

Definition at line 2134 of file PrimalDualHybridGradientParams.java.

◆ VERBOSITY_LEVEL_FIELD_NUMBER

final int com.google.ortools.pdlp.PrimalDualHybridGradientParams.VERBOSITY_LEVEL_FIELD_NUMBER = 26

static

Definition at line 1418 of file PrimalDualHybridGradientParams.java.

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

build/java/ortools-java/src/main/java/com/google/ortools/pdlp/PrimalDualHybridGradientParams.java

Classes

Public Member Functions

Static Public Member Functions

Static Public Attributes

Protected Member Functions

Detailed Description

Member Function Documentation

◆ equals()

◆ getAdaptiveLinesearchParameters()

◆ getAdaptiveLinesearchParametersOrBuilder()

◆ getDefaultInstance()

◆ getDefaultInstanceForType()

◆ getDescriptor()

◆ getDiagonalQpTrustRegionSolverTolerance()

◆ getHandleSomePrimalGradientsOnFiniteBoundsAsResiduals()

◆ getInfiniteConstraintBoundThreshold()

◆ getInitialPrimalWeight()

◆ getInitialStepSizeScaling()

◆ getL2NormRescaling()

◆ getLinesearchRule()

◆ getLInfRuizIterations()

◆ getLogIntervalSeconds()

◆ getMajorIterationFrequency()

◆ getMalitskyPockParameters()

◆ getMalitskyPockParametersOrBuilder()

◆ getNecessaryReductionForRestart()

◆ getNumShards()

◆ getNumThreads()

◆ getParserForType()

◆ getPresolveOptions()

◆ getPresolveOptionsOrBuilder()

◆ getPrimalWeightUpdateSmoothing()

◆ getRandomProjectionSeeds()

◆ getRandomProjectionSeedsCount()

◆ getRandomProjectionSeedsList()

◆ getRecordIterationStats()

◆ getRestartStrategy()

◆ getSchedulerType()

◆ getSerializedSize()

◆ getSufficientReductionForRestart()

◆ getTerminationCheckFrequency()

◆ getTerminationCriteria()

◆ getTerminationCriteriaOrBuilder()

◆ getUseDiagonalQpTrustRegionSolver()

◆ getUseFeasibilityPolishing()

◆ getVerbosityLevel()

◆ hasAdaptiveLinesearchParameters()

◆ hasDiagonalQpTrustRegionSolverTolerance()

◆ hasHandleSomePrimalGradientsOnFiniteBoundsAsResiduals()

◆ hashCode()

◆ hasInfiniteConstraintBoundThreshold()

◆ hasInitialPrimalWeight()

◆ hasInitialStepSizeScaling()

◆ hasL2NormRescaling()

◆ hasLinesearchRule()

◆ hasLInfRuizIterations()

◆ hasLogIntervalSeconds()

◆ hasMajorIterationFrequency()

◆ hasMalitskyPockParameters()

◆ hasNecessaryReductionForRestart()

◆ hasNumShards()

◆ hasNumThreads()

◆ hasPresolveOptions()

◆ hasPrimalWeightUpdateSmoothing()

◆ hasRecordIterationStats()

◆ hasRestartStrategy()

◆ hasSchedulerType()

◆ hasSufficientReductionForRestart()

◆ hasTerminationCheckFrequency()

◆ hasTerminationCriteria()

◆ hasUseDiagonalQpTrustRegionSolver()

◆ hasUseFeasibilityPolishing()

◆ hasVerbosityLevel()

◆ internalGetFieldAccessorTable()

◆ isInitialized()

◆ newBuilder() [1/2]

◆ newBuilder() [2/2]

◆ newBuilderForType() [1/2]

◆ newBuilderForType() [2/2]

◆ parseDelimitedFrom() [1/2]