Package 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
    Description
    MPSosConstraint.Type
    getType()
    optional .operations_research.MPSosConstraint.Type type = 1 [default = SOS1_DEFAULT];
    int
    getVarIndex(int index)
    Variable index (w.r.t.
    int
    getVarIndexCount()
    Variable index (w.r.t.
    List<Integer>
    getVarIndexList()
    Variable index (w.r.t.
    double
    getWeight(int index)
    Optional: SOS weights.
    int
    getWeightCount()
    Optional: SOS weights.
    List<Double>
    getWeightList()
    Optional: SOS weights.
    boolean
    hasType()
    optional .operations_research.MPSosConstraint.Type type = 1 [default = SOS1_DEFAULT];

    Methods inherited from interface com.google.protobuf.MessageLiteOrBuilder

    isInitialized

    Methods inherited from interface com.google.protobuf.MessageOrBuilder

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

  • Method Details

    • 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

      List<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

      List<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.