Class HowardMinimumMeanCycle<V,E>

java.lang.Object
org.jgrapht.alg.cycle.HowardMinimumMeanCycle<V,E>
Type Parameters:
V - graph vertex type
E - graph edge type
All Implemented Interfaces:
MinimumCycleMeanAlgorithm<V,E>

public class HowardMinimumMeanCycle<V,E> extends Object implements MinimumCycleMeanAlgorithm<V,E>
Implementation of Howard`s algorithm for finding minimum cycle mean in a graph.

The algorithm is described in the article: Ali Dasdan, Sandy S. Irani, and Rajesh K. Gupta. 1999. Efficient algorithms for optimum cycle mean and optimum cost to time ratio problems. In Proceedings of the 36th annual ACM/IEEE Design Automation Conference (DAC ’99). Association for Computing Machinery, New York, NY, USA, 37–42. DOI:https://doi.org/10.1145/309847.309862

Firstly, the graph is divided into strongly connected components. The minimum cycle mean is then computed as the globally minimum cycle mean over all components. In the process the necessary information is recorded to be able to reconstruct the cycle with minimum mean.

The computations are divided into iterations. In each iteration the algorithm tries to update current minimum cycle mean value. There is a possibility to limit the total number of iteration via a constructor parameter.

Author:
Semen Chudakov
  • Constructor Details

    • HowardMinimumMeanCycle

      public HowardMinimumMeanCycle(Graph<V,E> graph)
      Constructs an instance of the algorithm for the given graph.
      Parameters:
      graph - graph
    • HowardMinimumMeanCycle

      public HowardMinimumMeanCycle(Graph<V,E> graph, int maximumIterations)
      Constructs an instance of the algorithm for the given graph and maximumIterations.
      Parameters:
      graph - graph
      maximumIterations - maximum number of iterations
    • HowardMinimumMeanCycle

      public HowardMinimumMeanCycle(Graph<V,E> graph, int maximumIterations, StrongConnectivityAlgorithm<V,E> strongConnectivityAlgorithm, double toleranceEpsilon)
      Constructs an instance of the algorithm for the given graph, maximumIterations, strongConnectivityAlgorithm and toleranceEpsilon.
      Parameters:
      graph - graph
      maximumIterations - maximum number of iterations
      strongConnectivityAlgorithm - algorithm to compute strongly connected components
      toleranceEpsilon - tolerance to compare floating point numbers
  • Method Details