Partitioning a graph with a parallel genetic algorithm

  • Gregor von Laszewski
  • Heinz Mühlenbein
Genetic Algorithms Parallel Implementations Of Genetic Algorithms
Part of the Lecture Notes in Computer Science book series (LNCS, volume 496)

Abstract

We present a parallel genetic algorithm for the k way graph partitioning problem. The algorithm uses selection in local neighborhood and sophisticated genetic operators. For a sample problem the algorithm has found better solutions than those found by recent GPP algorithms. The success of the parallel genetic algorithm depends on the representation, a suitable crossover operator and an efficient local hill climbing method which is used to restrict the solution space.

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Copyright information

© Springer-Verlag 1991

Authors and Affiliations

  • Gregor von Laszewski
    • 1
  • Heinz Mühlenbein
    • 2
  1. 1.The Ohio-State University, CISColumbus
  2. 2.Gesellschaft für Mathematik und DatenverarbeitungSt. AugustinGermany

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