Class KolmogorovWeightedMatching<V,E>

java.lang.Object
org.jgrapht.alg.matching.blossom.v5.KolmogorovWeightedMatching<V,E>
Type Parameters:
V - the graph vertex type
E - the graph edge type
All Implemented Interfaces:
MatchingAlgorithm<V,E>

public class KolmogorovWeightedMatching<V,E> extends Object implements MatchingAlgorithm<V,E>
This class computes weighted matchings in general graphs. Depending on the constructor parameter the weight of the resulting matching is maximized or minimized. If maximum of minimum weight perfect algorithm is needed, see KolmogorovWeightedPerfectMatching.

This class reduces both maximum and minimum weight matching problems to the maximum and minimum weight perfect matching problems correspondingly. See KolmogorovWeightedPerfectMatching for relative definitions and algorithm description

Author:
Timofey Chudakov
See Also:
  • Constructor Details

    • KolmogorovWeightedMatching

      public KolmogorovWeightedMatching(Graph<V,E> initialGraph)
      Constructs a new instance of the algorithm using the default options. The goal of the constructed algorithm is to minimize the weight of the resulting matching.
      Parameters:
      initialGraph - the graph for which to find a weighted matching
    • KolmogorovWeightedMatching

      public KolmogorovWeightedMatching(Graph<V,E> initialGraph, ObjectiveSense objectiveSense)
      Constructs a new instance of the algorithm using the default options. The goal of the constructed algorithm is to maximize or minimize the weight of the resulting matching depending on the maximize parameter.
      Parameters:
      initialGraph - the graph for which to find a weighted matching
      objectiveSense - objective sense of the algorithm
    • KolmogorovWeightedMatching

      public KolmogorovWeightedMatching(Graph<V,E> initialGraph, BlossomVOptions options)
      Constructs a new instance of the algorithm with the specified options. The goal of the constructed algorithm is to minimize the weight of the resulting matching.
      Parameters:
      initialGraph - the graph for which to find a weighted matching
      options - the options which define the strategies for the initialization and dual updates
    • KolmogorovWeightedMatching

      public KolmogorovWeightedMatching(Graph<V,E> initialGraph, BlossomVOptions options, ObjectiveSense objectiveSense)
      Constructs a new instance of the algorithm with the specified options. The goal of the constructed algorithm is to maximize or minimize the weight of the resulting matching depending on the maximize parameter.
      Parameters:
      initialGraph - the graph for which to find a weighted matching
      options - the options which define the strategies for the initialization and dual updates
      objectiveSense - objective sense of the algorithm
  • Method Details

    • getMatching

      public MatchingAlgorithm.Matching<V,E> getMatching()
      Computes and returns a matching of maximum or minimum weight in the initialGraph depending on the goal of the algorithm.
      Specified by:
      getMatching in interface MatchingAlgorithm<V,E>
      Returns:
      weighted matching in the initialGraph
    • testOptimality

      public boolean testOptimality()
      Performs an optimality test after the perfect matching is computed. This test is done via KolmogorovWeightedPerfectMatching.testOptimality()

      More precisely, checks whether dual variables of all pseudonodes and resulting slacks of all edges are non-negative and that slacks of all matched edges are exactly 0. Since the algorithm uses floating point arithmetic, this check is done with precision of KolmogorovWeightedPerfectMatching.EPS

      In general, this method should always return true unless the algorithm implementation has a bug.

      Returns:
      true iff the assigned dual variables satisfy the dual linear program formulation AND complementary slackness conditions are also satisfied. The total error must not exceed EPS
    • getError

      public double getError()
      Computes the error in the solution to the dual linear program. This computation is done via KolmogorovWeightedPerfectMatching.getError(). More precisely, the total error equals the sum of:
      • Absolute value of edge slack if negative or the edge is matched
      • Absolute value of pseudonode variable if negative
      Returns:
      the total numeric error