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Towards an optimal mutation probability for genetic algorithms

  • Genetic Algorithms
  • Conference paper
  • First Online:
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

In this paper the optimal parameter setting of Genetic Algorithms (GAs) is investigated. Particular attention has been paid to the dependence of the mutation probability P M upon two parameters, the dimension of the configuration space l and the population size M. Assuming strict conditions on both the problem to be optimized and the GA, P M converges to 0 as the population size M or the dimension of the configuration space l converges to infinity. For direct application a heuristic comprising these results is presented. The parameter settings obtained by applying this heuristic are in accordance with those which have been obtained earlier by experiment.

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Authors and Affiliations

  1. Physics Institute, University of Heidelberg, Philosophenweg 12, D-6900, Heidelberg, Germany

    Jürgen Hesser & Reinhard Männer

Authors
  1. Jürgen Hesser
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  2. Reinhard Männer
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Editor information

Hans-Paul Schwefel Reinhard Männer

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© 1991 Springer-Verlag Berlin Heidelberg

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Hesser, J., Männer, R. (1991). Towards an optimal mutation probability for genetic algorithms. 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/BFb0029727

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  • DOI: https://doi.org/10.1007/BFb0029727

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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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