com.google.ortools.linearsolver

Interface MPSosConstraintOrBuilder

All Superinterfaces:

com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder

All Known Implementing Classes:

MPSosConstraint, MPSosConstraint.Builder

public interface MPSosConstraintOrBuilder
extends com.google.protobuf.MessageOrBuilder

Method Summary

Modifier and Type	Method and Description
MPSosConstraint.Type	getType() optional .operations_research.MPSosConstraint.Type type = 1 [default = SOS1_DEFAULT];
int	getVarIndex(int index) Variable index (w.r.t. the "variable" field of MPModelProto) of the variables in the SOS.
int	getVarIndexCount() Variable index (w.r.t. the "variable" field of MPModelProto) of the variables in the SOS.
java.util.List<java.lang.Integer>	getVarIndexList() Variable index (w.r.t. the "variable" field of MPModelProto) of the variables in the SOS.
double	getWeight(int index) Optional: SOS weights.
int	getWeightCount() Optional: SOS weights.
java.util.List<java.lang.Double>	getWeightList() Optional: SOS weights.
boolean	hasType() optional .operations_research.MPSosConstraint.Type type = 1 [default = SOS1_DEFAULT];

Methods inherited from interface com.google.protobuf.MessageOrBuilder

findInitializationErrors, getAllFields, getDefaultInstanceForType, getDescriptorForType, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof

Methods inherited from interface com.google.protobuf.MessageLiteOrBuilder

isInitialized

Method Detail

hasType

boolean hasType()

optional .operations_research.MPSosConstraint.Type type = 1 [default = SOS1_DEFAULT];

Returns:

Whether the type field is set.

getType

MPSosConstraint.Type getType()

optional .operations_research.MPSosConstraint.Type type = 1 [default = SOS1_DEFAULT];

Returns:

The type.

getVarIndexList

java.util.List<java.lang.Integer> getVarIndexList()

 Variable index (w.r.t. the "variable" field of MPModelProto) of the
 variables in the SOS.
 

repeated int32 var_index = 2;

Returns:

A list containing the varIndex.

getVarIndexCount

int getVarIndexCount()

 Variable index (w.r.t. the "variable" field of MPModelProto) of the
 variables in the SOS.
 

repeated int32 var_index = 2;

Returns:

The count of varIndex.

getVarIndex

int getVarIndex(int index)

 Variable index (w.r.t. the "variable" field of MPModelProto) of the
 variables in the SOS.
 

repeated int32 var_index = 2;

Parameters:

index - The index of the element to return.

Returns:

The varIndex at the given index.

getWeightList

java.util.List<java.lang.Double> getWeightList()

 Optional: SOS weights. If non-empty, must be of the same size as
 "var_index", and strictly increasing. If empty and required by the
 underlying solver, the 1..n sequence will be given as weights.
 SUBTLE: The weights can help the solver make branch-and-bound decisions
 that fit the underlying optimization model: after each LP relaxation, it
 will compute the "average weight" of the SOS variables, weighted by value
 (this is confusing: here we're using the values as weights), and the binary
 branch decision will be: is the non-zero variable above or below that?
 (weights are strictly monotonous, so the "cutoff" average weight
 corresponds to a "cutoff" index in the var_index sequence).
 

repeated double weight = 3;

Returns:

A list containing the weight.

getWeightCount

int getWeightCount()

 Optional: SOS weights. If non-empty, must be of the same size as
 "var_index", and strictly increasing. If empty and required by the
 underlying solver, the 1..n sequence will be given as weights.
 SUBTLE: The weights can help the solver make branch-and-bound decisions
 that fit the underlying optimization model: after each LP relaxation, it
 will compute the "average weight" of the SOS variables, weighted by value
 (this is confusing: here we're using the values as weights), and the binary
 branch decision will be: is the non-zero variable above or below that?
 (weights are strictly monotonous, so the "cutoff" average weight
 corresponds to a "cutoff" index in the var_index sequence).
 

repeated double weight = 3;

Returns:

The count of weight.

getWeight

double getWeight(int index)

 Optional: SOS weights. If non-empty, must be of the same size as
 "var_index", and strictly increasing. If empty and required by the
 underlying solver, the 1..n sequence will be given as weights.
 SUBTLE: The weights can help the solver make branch-and-bound decisions
 that fit the underlying optimization model: after each LP relaxation, it
 will compute the "average weight" of the SOS variables, weighted by value
 (this is confusing: here we're using the values as weights), and the binary
 branch decision will be: is the non-zero variable above or below that?
 (weights are strictly monotonous, so the "cutoff" average weight
 corresponds to a "cutoff" index in the var_index sequence).
 

repeated double weight = 3;

Parameters:

index - The index of the element to return.

Returns:

The weight at the given index.