operations_research.pdlp.SolveLogOuterClass.InfeasibilityInformationOrBuilder Interface Reference

Inheritance diagram for operations_research.pdlp.SolveLogOuterClass.InfeasibilityInformationOrBuilder:

Public Member Functions
boolean	hasMaxPrimalRayInfeasibility ()
double	getMaxPrimalRayInfeasibility ()
boolean	hasPrimalRayLinearObjective ()
double	getPrimalRayLinearObjective ()
boolean	hasPrimalRayQuadraticNorm ()
double	getPrimalRayQuadraticNorm ()
boolean	hasMaxDualRayInfeasibility ()
double	getMaxDualRayInfeasibility ()
boolean	hasDualRayObjective ()
double	getDualRayObjective ()
boolean	hasCandidateType ()
operations_research.pdlp.SolveLogOuterClass.PointType	getCandidateType ()

Detailed Description

Definition at line 7199 of file SolveLogOuterClass.java.

Member Function Documentation

getCandidateType()

operations_research.pdlp.SolveLogOuterClass.PointType operations_research.pdlp.SolveLogOuterClass.InfeasibilityInformationOrBuilder.getCandidateType

(

)

Type of the point used to compute the InfeasibilityInformation.

optional .operations_research.pdlp.PointType candidate_type = 6;

Returns

The candidateType.

Implemented in operations_research.pdlp.SolveLogOuterClass.InfeasibilityInformation, and operations_research.pdlp.SolveLogOuterClass.InfeasibilityInformation.Builder.

getDualRayObjective()

double operations_research.pdlp.SolveLogOuterClass.InfeasibilityInformationOrBuilder.getDualRayObjective

(

)

The objective of the linear program labeled (1) in the previous paragraph.

optional double dual_ray_objective = 5;

Returns

The dualRayObjective.

Implemented in operations_research.pdlp.SolveLogOuterClass.InfeasibilityInformation, and operations_research.pdlp.SolveLogOuterClass.InfeasibilityInformation.Builder.

getMaxDualRayInfeasibility()

double operations_research.pdlp.SolveLogOuterClass.InfeasibilityInformationOrBuilder.getMaxDualRayInfeasibility

(

)

Let (y_ray, r_ray) be the algorithm's estimate of the dual and reduced cost
extreme ray where (y_ray, r_ray) is a vector (satisfying the dual variable
constraints) scaled such that its infinity norm is one. A simple and
typical choice of y_ray is (y_ray, r_ray) = (y, r) / max(| y |_∞, | r |_∞)
where y is the current dual iterate and r is the current dual reduced
costs. Consider the quadratic program we are solving but with the objective
(both quadratic and linear terms) set to zero. This forms a linear program
(label this linear program (1)) with no objective. Take the dual of (1) and
compute the maximum absolute value of the constraint error for
(y_ray, r_ray) to obtain the value of max_dual_ray_infeasibility.

optional double max_dual_ray_infeasibility = 4;

Returns

The maxDualRayInfeasibility.

Implemented in operations_research.pdlp.SolveLogOuterClass.InfeasibilityInformation, and operations_research.pdlp.SolveLogOuterClass.InfeasibilityInformation.Builder.

getMaxPrimalRayInfeasibility()

double operations_research.pdlp.SolveLogOuterClass.InfeasibilityInformationOrBuilder.getMaxPrimalRayInfeasibility

(

)

Let x_ray be the algorithm's estimate of the primal extreme ray where x_ray
is a vector that satisfies the sign constraints for a ray, scaled such that
its infinity norm is one (the sign constraints are the variable bound
constraints, with all finite bounds mapped to zero). A simple and typical
choice of x_ray is x_ray = x / | x |_∞ where x is the current primal
iterate projected onto the primal ray sign constraints. For this value
compute the maximum absolute error in the primal linear program with the
right hand side set to zero.

optional double max_primal_ray_infeasibility = 1;

Returns

The maxPrimalRayInfeasibility.

Implemented in operations_research.pdlp.SolveLogOuterClass.InfeasibilityInformation, and operations_research.pdlp.SolveLogOuterClass.InfeasibilityInformation.Builder.

getPrimalRayLinearObjective()

double operations_research.pdlp.SolveLogOuterClass.InfeasibilityInformationOrBuilder.getPrimalRayLinearObjective

(

)

The value of the linear part of the primal objective (ignoring additive
constants) evaluated at x_ray, i.e., c' * x_ray where c is the objective
coefficient vector.

optional double primal_ray_linear_objective = 2;

Returns

The primalRayLinearObjective.

Implemented in operations_research.pdlp.SolveLogOuterClass.InfeasibilityInformation, and operations_research.pdlp.SolveLogOuterClass.InfeasibilityInformation.Builder.

getPrimalRayQuadraticNorm()

double operations_research.pdlp.SolveLogOuterClass.InfeasibilityInformationOrBuilder.getPrimalRayQuadraticNorm

(

)

The l_∞ norm of the vector resulting from taking the quadratic matrix from
primal objective and multiplying it by the primal variables. For linear
programming problems this is zero.

optional double primal_ray_quadratic_norm = 3;

Returns

The primalRayQuadraticNorm.

Implemented in operations_research.pdlp.SolveLogOuterClass.InfeasibilityInformation, and operations_research.pdlp.SolveLogOuterClass.InfeasibilityInformation.Builder.

hasCandidateType()

boolean operations_research.pdlp.SolveLogOuterClass.InfeasibilityInformationOrBuilder.hasCandidateType

(

)

Type of the point used to compute the InfeasibilityInformation.

optional .operations_research.pdlp.PointType candidate_type = 6;

Returns

Whether the candidateType field is set.

Implemented in operations_research.pdlp.SolveLogOuterClass.InfeasibilityInformation, and operations_research.pdlp.SolveLogOuterClass.InfeasibilityInformation.Builder.

hasDualRayObjective()

boolean operations_research.pdlp.SolveLogOuterClass.InfeasibilityInformationOrBuilder.hasDualRayObjective

(

)

The objective of the linear program labeled (1) in the previous paragraph.

optional double dual_ray_objective = 5;

Returns

Whether the dualRayObjective field is set.

Implemented in operations_research.pdlp.SolveLogOuterClass.InfeasibilityInformation, and operations_research.pdlp.SolveLogOuterClass.InfeasibilityInformation.Builder.

hasMaxDualRayInfeasibility()

boolean operations_research.pdlp.SolveLogOuterClass.InfeasibilityInformationOrBuilder.hasMaxDualRayInfeasibility

(

)

Let (y_ray, r_ray) be the algorithm's estimate of the dual and reduced cost
extreme ray where (y_ray, r_ray) is a vector (satisfying the dual variable
constraints) scaled such that its infinity norm is one. A simple and
typical choice of y_ray is (y_ray, r_ray) = (y, r) / max(| y |_∞, | r |_∞)
where y is the current dual iterate and r is the current dual reduced
costs. Consider the quadratic program we are solving but with the objective
(both quadratic and linear terms) set to zero. This forms a linear program
(label this linear program (1)) with no objective. Take the dual of (1) and
compute the maximum absolute value of the constraint error for
(y_ray, r_ray) to obtain the value of max_dual_ray_infeasibility.

optional double max_dual_ray_infeasibility = 4;

Returns

Whether the maxDualRayInfeasibility field is set.

Implemented in operations_research.pdlp.SolveLogOuterClass.InfeasibilityInformation, and operations_research.pdlp.SolveLogOuterClass.InfeasibilityInformation.Builder.

hasMaxPrimalRayInfeasibility()

boolean operations_research.pdlp.SolveLogOuterClass.InfeasibilityInformationOrBuilder.hasMaxPrimalRayInfeasibility

(

)

Let x_ray be the algorithm's estimate of the primal extreme ray where x_ray
is a vector that satisfies the sign constraints for a ray, scaled such that
its infinity norm is one (the sign constraints are the variable bound
constraints, with all finite bounds mapped to zero). A simple and typical
choice of x_ray is x_ray = x / | x |_∞ where x is the current primal
iterate projected onto the primal ray sign constraints. For this value
compute the maximum absolute error in the primal linear program with the
right hand side set to zero.

optional double max_primal_ray_infeasibility = 1;

Returns

Whether the maxPrimalRayInfeasibility field is set.

Implemented in operations_research.pdlp.SolveLogOuterClass.InfeasibilityInformation, and operations_research.pdlp.SolveLogOuterClass.InfeasibilityInformation.Builder.

hasPrimalRayLinearObjective()

boolean operations_research.pdlp.SolveLogOuterClass.InfeasibilityInformationOrBuilder.hasPrimalRayLinearObjective

(

)

The value of the linear part of the primal objective (ignoring additive
constants) evaluated at x_ray, i.e., c' * x_ray where c is the objective
coefficient vector.

optional double primal_ray_linear_objective = 2;

Returns

Whether the primalRayLinearObjective field is set.

Implemented in operations_research.pdlp.SolveLogOuterClass.InfeasibilityInformation, and operations_research.pdlp.SolveLogOuterClass.InfeasibilityInformation.Builder.

hasPrimalRayQuadraticNorm()

boolean operations_research.pdlp.SolveLogOuterClass.InfeasibilityInformationOrBuilder.hasPrimalRayQuadraticNorm

(

)

The l_∞ norm of the vector resulting from taking the quadratic matrix from
primal objective and multiplying it by the primal variables. For linear
programming problems this is zero.

optional double primal_ray_quadratic_norm = 3;

Returns

Whether the primalRayQuadraticNorm field is set.

Implemented in operations_research.pdlp.SolveLogOuterClass.InfeasibilityInformation, and operations_research.pdlp.SolveLogOuterClass.InfeasibilityInformation.Builder.

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

• build/java/ortools-java/src/main/java/operations_research/pdlp/SolveLogOuterClass.java