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, setUnknownFieldsProto3
findInitializationErrors, getInitializationErrorString, internalMergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, newUninitializedMessageException, toString
addAll, addAll, mergeDelimitedFrom, mergeDelimitedFrom, newUninitializedMessageException
equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
public 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.Builder
clear
in interface com.google.protobuf.MessageLite.Builder
clear
in class com.google.protobuf.GeneratedMessage.Builder<InfeasibilityInformation.Builder>
public com.google.protobuf.Descriptors.Descriptor getDescriptorForType()
getDescriptorForType
in interface com.google.protobuf.Message.Builder
getDescriptorForType
in interface com.google.protobuf.MessageOrBuilder
getDescriptorForType
in class com.google.protobuf.GeneratedMessage.Builder<InfeasibilityInformation.Builder>
public InfeasibilityInformation getDefaultInstanceForType()
getDefaultInstanceForType
in interface com.google.protobuf.MessageLiteOrBuilder
getDefaultInstanceForType
in interface com.google.protobuf.MessageOrBuilder
public InfeasibilityInformation build()
build
in interface com.google.protobuf.Message.Builder
build
in interface com.google.protobuf.MessageLite.Builder
public InfeasibilityInformation buildPartial()
buildPartial
in interface com.google.protobuf.Message.Builder
buildPartial
in interface com.google.protobuf.MessageLite.Builder
public InfeasibilityInformation.Builder mergeFrom(com.google.protobuf.Message other)
mergeFrom
in interface com.google.protobuf.Message.Builder
mergeFrom
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.MessageLiteOrBuilder
isInitialized
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.Builder
mergeFrom
in interface com.google.protobuf.MessageLite.Builder
mergeFrom
in class com.google.protobuf.AbstractMessage.Builder<InfeasibilityInformation.Builder>
java.io.IOException
public 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 InfeasibilityInformationOrBuilder
public 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 InfeasibilityInformationOrBuilder
public 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 InfeasibilityInformationOrBuilder
public 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 InfeasibilityInformationOrBuilder
public 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 InfeasibilityInformationOrBuilder
public 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 InfeasibilityInformationOrBuilder
public 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 InfeasibilityInformationOrBuilder
public 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 InfeasibilityInformationOrBuilder
public 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 InfeasibilityInformationOrBuilder
public double getDualRayObjective()
The objective of the linear program labeled (1) in the previous paragraph.
optional double dual_ray_objective = 5;
getDualRayObjective
in interface InfeasibilityInformationOrBuilder
public 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 InfeasibilityInformationOrBuilder
public PointType getCandidateType()
Type of the point used to compute the InfeasibilityInformation.
optional .operations_research.pdlp.PointType candidate_type = 6;
getCandidateType
in interface InfeasibilityInformationOrBuilder
public 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;
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