Google.OrTools.PDLP Namespace Reference

Classes
class	AdaptiveLinesearchParams
	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. More...
class	ConvergenceInformation
	Information measuring how close a candidate is to establishing feasibility and optimality; see also TerminationCriteria. More...
class	FeasibilityPolishingDetails
	Details about one primal feasibility or dual feasibility polishing phase within a solve with use_feasibility_polishing. See SolveLog for descriptions of the fields with the same name. More...
class	InfeasibilityInformation
	Information measuring how close a point is to establishing primal or dual infeasibility (i.e. has no solution); see also TerminationCriteria. More...
class	IterationStats
	All values in IterationStats assume that the primal quadratic program is a minimization problem and the dual is a maximization problem. Problems should be transformed to this form if they are not already in this form. The dual vector is defined to be the vector of multipliers on the linear constraints, that is, excluding dual multipliers on variable bounds (reduced costs). More...
class	MalitskyPockParams
class	PointMetadata
class	PrimalDualHybridGradientParams
	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: More...
class	QuadraticProgramStats
	Easy-to-compute statistics for the quadratic program. More...
class	SolveLog
class	SolveLogReflection
	Holder for reflection information generated from ortools/pdlp/solve_log.proto. More...
class	SolversReflection
	Holder for reflection information generated from ortools/pdlp/solvers.proto. More...
class	TerminationCriteria
	Relevant 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 infeasibility. (2) The termination criteria for Mosek's linear programming optimizer https://docs.mosek.com/9.0/pythonfusion/solving-linear.html. (3) The termination criteria for OSQP is in section 3.3 of https://web.stanford.edu/~boyd/papers/pdf/osqp.pdf. (4) The termination criteria for SCS is in section 3.5 of https://arxiv.org/pdf/1312.3039.pdf. More...

Enumerations
enum	RestartChoice { Unspecified = 0 , NoRestart = 1 , WeightedAverageReset = 2 , RestartToAverage = 3 }
	Specifies whether a restart was performed on a given iteration. More...
enum	PointType {   Unspecified = 0 , CurrentIterate = 1 , IterateDifference = 2 , AverageIterate = 3 ,   None = 4 , PresolverSolution = 5 , FeasibilityPolishingSolution = 6 }
	Identifies the type of point used to compute the fields in a given proto; see ConvergenceInformation and InfeasibilityInformation. More...
enum	TerminationReason {   Unspecified = 0 , Optimal = 1 , PrimalInfeasible = 2 , DualInfeasible = 3 ,   TimeLimit = 4 , IterationLimit = 5 , KktMatrixPassLimit = 8 , InterruptedByUser = 12 ,   NumericalError = 6 , InvalidProblem = 9 , InvalidInitialSolution = 13 , InvalidParameter = 10 ,   Other = 7 , PrimalOrDualInfeasible = 11 }
enum	PolishingPhaseType { Unspecified = 0 , PrimalFeasibility = 1 , DualFeasibility = 2 }
enum	OptimalityNorm { Unspecified = 0 , LInf = 1 , L2 = 2 , LInfComponentwise = 3 }

Enumeration Type Documentation

OptimalityNorm

enum Google.OrTools.PDLP.OptimalityNorm

Enumerator
Unspecified
LInf	The infinity norm.
L2	The Euclidean norm.
LInfComponentwise	The infinity norm of component-wise relative errors offset by the ratio of the absolute and relative error tolerances, i.e., the l_∞ norm of [residual / (eps_ratio + bound)], where eps_ratio = eps_optimal_{X}_residual_absolute / eps_optimal_{X}_residual_relative where {X} is either primal or dual, and bound is the corresponding primal or dual bound (that is, the violated constraint bound for primal residuals, and the objective coefficient for dual residuals). Using eps_ratio in this norm means that if the norm is <= eps_optimal_{X}_residual_relative, then the residuals satisfy residual <= eps_optimal_{X}_residual_absolute. eps_optimal_{X}_residual_relative * bound

Definition at line 118 of file Solvers.pb.cs.

PointType

enum Google.OrTools.PDLP.PointType

Identifies the type of point used to compute the fields in a given proto; see ConvergenceInformation and InfeasibilityInformation.

Enumerator
Unspecified
CurrentIterate	Current iterate (x_k, y_k).
IterateDifference	Difference of iterates (x_{k+1} - x_k, y_{k+1} - y_k).
AverageIterate	Average of iterates since the last restart.
None	There is no corresponding point.
PresolverSolution	Output of presolver.
FeasibilityPolishingSolution	Combined solution from primal and dual feasibility polishing.

Definition at line 188 of file SolveLog.pb.cs.

PolishingPhaseType

enum Google.OrTools.PDLP.PolishingPhaseType

Enumerator
Unspecified
PrimalFeasibility
DualFeasibility

Definition at line 254 of file SolveLog.pb.cs.

RestartChoice

enum Google.OrTools.PDLP.RestartChoice

Specifies whether a restart was performed on a given iteration.

Enumerator
Unspecified
NoRestart	No restart on this iteration.
WeightedAverageReset	The weighted average of iterates is cleared and reset to the current point. Note from a mathematical perspective this can be equivalently viewed as restarting the algorithm but picking the restart point to be the current iterate.
RestartToAverage	The algorithm is restarted at the average of iterates since the last restart.

Definition at line 164 of file SolveLog.pb.cs.

TerminationReason

enum Google.OrTools.PDLP.TerminationReason

Enumerator
Unspecified
Optimal
PrimalInfeasible	Note in this situation the dual could be either unbounded or infeasible.
DualInfeasible	Note in this situation the primal could be either unbounded or infeasible.
TimeLimit
IterationLimit
KktMatrixPassLimit
InterruptedByUser
NumericalError
InvalidProblem	Indicates that the solver detected invalid problem data, e.g., inconsistent bounds.
InvalidInitialSolution	Indicates that the solver detected that the initial solution that was provided was invalid, e.g., wrong size or containing NAN or inf.
InvalidParameter	Indicates that an invalid value for the parameters was detected.
Other
PrimalOrDualInfeasible	Primal or dual infeasibility was detected (e.g. by presolve) but no certificate is available.

Definition at line 216 of file SolveLog.pb.cs.