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AISB Workshop on Evolutionary Computing

AISB EC 1996: Evolutionary Computing pp 297–304Cite as

A comparative study of steady state and generational genetic algorithms for use in nonstationary environments

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1143))

Abstract

The objective of this study is a comparison of two models of a genetic algorithm — the generational and incremental/steady state genetic algorithms — for use in the nonstationary/dynamic environments. It is experimentally shown that selection of a suitable version of the genetic algorithm can improve performance of the genetic algorithm in such environments.This can extend ability of the genetic algorithm to track the environmental changes which are relatively small and occur with a low frequency without need to implement an additional technique for tracking changing optima.

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References

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Author information

Authors and Affiliations

  1. Faculty of Computer Studies and Mathematics, University of the West of England, BS16 1QY, Bristol, UK

    F. Vavak & T. C. Fogarty

Authors
  1. F. Vavak
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  2. T. C. Fogarty
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Editor information

Terence C. Fogarty

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© 1996 Springer-Verlag Berlin Heidelberg

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Vavak, F., Fogarty, T.C. (1996). A comparative study of steady state and generational genetic algorithms for use in nonstationary environments. In: Fogarty, T.C. (eds) Evolutionary Computing. AISB EC 1996. Lecture Notes in Computer Science, vol 1143. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0032791

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  • DOI: https://doi.org/10.1007/BFb0032791

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-61749-5

  • Online ISBN: 978-3-540-70671-7

  • eBook Packages: Springer Book Archive

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