public static final class InfeasibilityInformation.Builder extends com.google.protobuf.GeneratedMessage.Builder<InfeasibilityInformation.Builder> implements InfeasibilityInformationOrBuilder
Information measuring how close a point is to establishing primal or dual infeasibility (i.e. has no solution); see also TerminationCriteria.Protobuf type
operations_research.pdlp.InfeasibilityInformation| Modifier and Type | Method and Description |
|---|---|
InfeasibilityInformation |
build() |
InfeasibilityInformation |
buildPartial() |
InfeasibilityInformation.Builder |
clear() |
InfeasibilityInformation.Builder |
clearCandidateType()
Type of the point used to compute the InfeasibilityInformation.
|
InfeasibilityInformation.Builder |
clearDualRayObjective()
The objective of the linear program labeled (1) in the previous paragraph.
|
InfeasibilityInformation.Builder |
clearMaxDualRayInfeasibility()
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.
|
InfeasibilityInformation.Builder |
clearMaxPrimalRayInfeasibility()
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).
|
InfeasibilityInformation.Builder |
clearPrimalRayLinearObjective()
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.
|
InfeasibilityInformation.Builder |
clearPrimalRayQuadraticNorm()
The l_∞ norm of the vector resulting from taking the quadratic matrix from
primal objective and multiplying it by the primal variables.
|
PointType |
getCandidateType()
Type of the point used to compute the InfeasibilityInformation.
|
InfeasibilityInformation |
getDefaultInstanceForType() |
static com.google.protobuf.Descriptors.Descriptor |
getDescriptor() |
com.google.protobuf.Descriptors.Descriptor |
getDescriptorForType() |
double |
getDualRayObjective()
The objective of the linear program labeled (1) in the previous paragraph.
|
double |
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.
|
double |
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).
|
double |
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.
|
double |
getPrimalRayQuadraticNorm()
The l_∞ norm of the vector resulting from taking the quadratic matrix from
primal objective and multiplying it by the primal variables.
|
boolean |
hasCandidateType()
Type of the point used to compute the InfeasibilityInformation.
|
boolean |
hasDualRayObjective()
The objective of the linear program labeled (1) in the previous paragraph.
|
boolean |
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.
|
boolean |
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).
|
boolean |
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.
|
boolean |
hasPrimalRayQuadraticNorm()
The l_∞ norm of the vector resulting from taking the quadratic matrix from
primal objective and multiplying it by the primal variables.
|
protected com.google.protobuf.GeneratedMessage.FieldAccessorTable |
internalGetFieldAccessorTable() |
boolean |
isInitialized() |
InfeasibilityInformation.Builder |
mergeFrom(com.google.protobuf.CodedInputStream input,
com.google.protobuf.ExtensionRegistryLite extensionRegistry) |
InfeasibilityInformation.Builder |
mergeFrom(InfeasibilityInformation other) |
InfeasibilityInformation.Builder |
mergeFrom(com.google.protobuf.Message other) |
InfeasibilityInformation.Builder |
setCandidateType(PointType value)
Type of the point used to compute the InfeasibilityInformation.
|
InfeasibilityInformation.Builder |
setDualRayObjective(double value)
The objective of the linear program labeled (1) in the previous paragraph.
|
InfeasibilityInformation.Builder |
setMaxDualRayInfeasibility(double value)
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.
|
InfeasibilityInformation.Builder |
setMaxPrimalRayInfeasibility(double value)
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).
|
InfeasibilityInformation.Builder |
setPrimalRayLinearObjective(double value)
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.
|
InfeasibilityInformation.Builder |
setPrimalRayQuadraticNorm(double value)
The l_∞ norm of the vector resulting from taking the quadratic matrix from
primal objective and multiplying it by the primal variables.
|
addRepeatedField, clearField, clearOneof, clone, getAllFields, getField, getFieldBuilder, getOneofFieldDescriptor, getParentForChildren, getRepeatedField, getRepeatedFieldBuilder, getRepeatedFieldCount, getUnknownFields, getUnknownFieldSetBuilder, hasField, hasOneof, internalGetMapField, internalGetMapFieldReflection, internalGetMutableMapField, internalGetMutableMapFieldReflection, isClean, markClean, mergeUnknownFields, mergeUnknownLengthDelimitedField, mergeUnknownVarintField, newBuilderForField, onBuilt, onChanged, parseUnknownField, setField, setRepeatedField, setUnknownFields, setUnknownFieldSetBuilder, setUnknownFieldsProto3findInitializationErrors, getInitializationErrorString, internalMergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, newUninitializedMessageException, toStringaddAll, addAll, mergeDelimitedFrom, mergeDelimitedFrom, newUninitializedMessageExceptionequals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, waitpublic static final com.google.protobuf.Descriptors.Descriptor getDescriptor()
protected com.google.protobuf.GeneratedMessage.FieldAccessorTable internalGetFieldAccessorTable()
internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessage.Builder<InfeasibilityInformation.Builder>public InfeasibilityInformation.Builder clear()
clear in interface com.google.protobuf.Message.Builderclear in interface com.google.protobuf.MessageLite.Builderclear in class com.google.protobuf.GeneratedMessage.Builder<InfeasibilityInformation.Builder>public com.google.protobuf.Descriptors.Descriptor getDescriptorForType()
getDescriptorForType in interface com.google.protobuf.Message.BuildergetDescriptorForType in interface com.google.protobuf.MessageOrBuildergetDescriptorForType in class com.google.protobuf.GeneratedMessage.Builder<InfeasibilityInformation.Builder>public InfeasibilityInformation getDefaultInstanceForType()
getDefaultInstanceForType in interface com.google.protobuf.MessageLiteOrBuildergetDefaultInstanceForType in interface com.google.protobuf.MessageOrBuilderpublic InfeasibilityInformation build()
build in interface com.google.protobuf.Message.Builderbuild in interface com.google.protobuf.MessageLite.Builderpublic InfeasibilityInformation buildPartial()
buildPartial in interface com.google.protobuf.Message.BuilderbuildPartial in interface com.google.protobuf.MessageLite.Builderpublic InfeasibilityInformation.Builder mergeFrom(com.google.protobuf.Message other)
mergeFrom in interface com.google.protobuf.Message.BuildermergeFrom in class com.google.protobuf.AbstractMessage.Builder<InfeasibilityInformation.Builder>public InfeasibilityInformation.Builder mergeFrom(InfeasibilityInformation other)
public final boolean isInitialized()
isInitialized in interface com.google.protobuf.MessageLiteOrBuilderisInitialized in class com.google.protobuf.GeneratedMessage.Builder<InfeasibilityInformation.Builder>public InfeasibilityInformation.Builder mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws java.io.IOException
mergeFrom in interface com.google.protobuf.Message.BuildermergeFrom in interface com.google.protobuf.MessageLite.BuildermergeFrom in class com.google.protobuf.AbstractMessage.Builder<InfeasibilityInformation.Builder>java.io.IOExceptionpublic boolean 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;hasMaxPrimalRayInfeasibility in interface InfeasibilityInformationOrBuilderpublic double 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;getMaxPrimalRayInfeasibility in interface InfeasibilityInformationOrBuilderpublic InfeasibilityInformation.Builder setMaxPrimalRayInfeasibility(double value)
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;value - The maxPrimalRayInfeasibility to set.public InfeasibilityInformation.Builder clearMaxPrimalRayInfeasibility()
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;public boolean 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;hasPrimalRayLinearObjective in interface InfeasibilityInformationOrBuilderpublic double 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;getPrimalRayLinearObjective in interface InfeasibilityInformationOrBuilderpublic InfeasibilityInformation.Builder setPrimalRayLinearObjective(double value)
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;value - The primalRayLinearObjective to set.public InfeasibilityInformation.Builder clearPrimalRayLinearObjective()
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;public boolean 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;hasPrimalRayQuadraticNorm in interface InfeasibilityInformationOrBuilderpublic double 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;getPrimalRayQuadraticNorm in interface InfeasibilityInformationOrBuilderpublic InfeasibilityInformation.Builder setPrimalRayQuadraticNorm(double value)
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;value - The primalRayQuadraticNorm to set.public InfeasibilityInformation.Builder clearPrimalRayQuadraticNorm()
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;public boolean 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;hasMaxDualRayInfeasibility in interface InfeasibilityInformationOrBuilderpublic double 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;getMaxDualRayInfeasibility in interface InfeasibilityInformationOrBuilderpublic InfeasibilityInformation.Builder setMaxDualRayInfeasibility(double value)
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;value - The maxDualRayInfeasibility to set.public InfeasibilityInformation.Builder clearMaxDualRayInfeasibility()
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;public boolean hasDualRayObjective()
The objective of the linear program labeled (1) in the previous paragraph.
optional double dual_ray_objective = 5;hasDualRayObjective in interface InfeasibilityInformationOrBuilderpublic double getDualRayObjective()
The objective of the linear program labeled (1) in the previous paragraph.
optional double dual_ray_objective = 5;getDualRayObjective in interface InfeasibilityInformationOrBuilderpublic InfeasibilityInformation.Builder setDualRayObjective(double value)
The objective of the linear program labeled (1) in the previous paragraph.
optional double dual_ray_objective = 5;value - The dualRayObjective to set.public InfeasibilityInformation.Builder clearDualRayObjective()
The objective of the linear program labeled (1) in the previous paragraph.
optional double dual_ray_objective = 5;public boolean hasCandidateType()
Type of the point used to compute the InfeasibilityInformation.
optional .operations_research.pdlp.PointType candidate_type = 6;hasCandidateType in interface InfeasibilityInformationOrBuilderpublic PointType getCandidateType()
Type of the point used to compute the InfeasibilityInformation.
optional .operations_research.pdlp.PointType candidate_type = 6;getCandidateType in interface InfeasibilityInformationOrBuilderpublic InfeasibilityInformation.Builder setCandidateType(PointType value)
Type of the point used to compute the InfeasibilityInformation.
optional .operations_research.pdlp.PointType candidate_type = 6;value - The candidateType to set.public InfeasibilityInformation.Builder clearCandidateType()
Type of the point used to compute the InfeasibilityInformation.
optional .operations_research.pdlp.PointType candidate_type = 6;Copyright © 2024. All rights reserved.