Package com.google.ortools.pdlp
package com.google.ortools.pdlp
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ClassDescriptionAt the end of each iteration, regardless of whether the step was accepted or not, the adaptive rule updates the step_size as the minimum of two potential step sizes defined by the following two exponents.At the end of each iteration, regardless of whether the step was accepted or not, the adaptive rule updates the step_size as the minimum of two potential step sizes defined by the following two exponents.Information measuring how close a candidate is to establishing feasibility and optimality; see also TerminationCriteria.Information measuring how close a candidate is to establishing feasibility and optimality; see also TerminationCriteria.Details about one primal feasibility or dual feasibility polishing phase within a solve with `use_feasibility_polishing`.Details about one primal feasibility or dual feasibility polishing phase within a solve with `use_feasibility_polishing`.Information measuring how close a point is to establishing primal or dual infeasibility (i.e. has no solution); see also TerminationCriteria.Information measuring how close a point is to establishing primal or dual infeasibility (i.e. has no solution); see also TerminationCriteria.All values in IterationStats assume that the primal quadratic program is a minimization problem and the dual is a maximization problem.All values in IterationStats assume that the primal quadratic program is a minimization problem and the dual is a maximization problem.Protobuf type
operations_research.pdlp.MalitskyPockParamsProtobuf typeoperations_research.pdlp.MalitskyPockParamsProtobuf enumoperations_research.pdlp.OptimalityNormProtobuf typeoperations_research.pdlp.PointMetadataProtobuf typeoperations_research.pdlp.PointMetadataIdentifies the type of point used to compute the fields in a given proto; see ConvergenceInformation and InfeasibilityInformation.Protobuf enumoperations_research.pdlp.PolishingPhaseTypeParameters for PrimalDualHybridGradient() in primal_dual_hybrid_gradient.h.Parameters for PrimalDualHybridGradient() in primal_dual_hybrid_gradient.h.Protobuf enumoperations_research.pdlp.PrimalDualHybridGradientParams.LinesearchRuleProtobuf typeoperations_research.pdlp.PrimalDualHybridGradientParams.PresolveOptionsProtobuf typeoperations_research.pdlp.PrimalDualHybridGradientParams.PresolveOptionsProtobuf enumoperations_research.pdlp.PrimalDualHybridGradientParams.RestartStrategyEasy-to-compute statistics for the quadratic program.Easy-to-compute statistics for the quadratic program.Specifies whether a restart was performed on a given iteration.The type of system used to schedule CPU threads to do work in parallel.Protobuf typeoperations_research.pdlp.SolveLogProtobuf typeoperations_research.pdlp.SolveLogRelevant readings on infeasibility certificates: (1) https://docs.mosek.com/modeling-cookbook/qcqo.html provides references explaining why the primal rays imply dual infeasibility and dual rays imply primal infeasibilityRelevant readings on infeasibility certificates: (1) https://docs.mosek.com/modeling-cookbook/qcqo.html provides references explaining why the primal rays imply dual infeasibility and dual rays imply primal infeasibilityProtobuf typeoperations_research.pdlp.TerminationCriteria.DetailedOptimalityCriteriaProtobuf typeoperations_research.pdlp.TerminationCriteria.DetailedOptimalityCriteriaProtobuf typeoperations_research.pdlp.TerminationCriteria.SimpleOptimalityCriteriaProtobuf typeoperations_research.pdlp.TerminationCriteria.SimpleOptimalityCriteriaProtobuf enumoperations_research.pdlp.TerminationReason