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Partitioning a graph with a parallel genetic algorithm

  • Genetic Algorithms
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Parallel Problem Solving from Nature (PPSN 1990)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 496))

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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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Author information

Authors and Affiliations

  1. The Ohio-State University, CIS, 2036 Neil Avenue, 43210-1227, Columbus, Ohio

    Gregor von Laszewski

  2. Gesellschaft für Mathematik und Datenverarbeitung, W-5205, St. Augustin, Germany

    Heinz Mühlenbein

Authors
  1. Gregor von Laszewski
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  2. Heinz Mühlenbein
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Editor information

Hans-Paul Schwefel Reinhard Männer

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© 1991 Springer-Verlag Berlin Heidelberg

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von Laszewski, G., Mühlenbein, H. (1991). Partitioning a graph with a parallel genetic algorithm. In: Schwefel, HP., Männer, R. (eds) Parallel Problem Solving from Nature. PPSN 1990. Lecture Notes in Computer Science, vol 496. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0029748

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  • DOI: https://doi.org/10.1007/BFb0029748

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-54148-6

  • Online ISBN: 978-3-540-70652-6

  • eBook Packages: Springer Book Archive

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