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Theoretical Aspects of Evolutionary Computing pp 59–85Cite as

Modelling Genetic Algorithm Dynamics

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Part of the book series: Natural Computing Series ((NCS))

Abstract

This tutorial is an introduction to the mathematical modelling of the dynamics of genetic algorithms (GAs). The distinguishing feature of this approach is that we consider macroscopic properties of the system. After some brief introductory remarks, we look at a generational GA, with tournament selection, tackling the ones-counting problem. Initially we ignore recombination. We start with a two-parameter model of the evolution. This is sufficient to explain the qualitative features of the dynamics, although it does not give a good quantitative agreement with simulations. We show how the agreement can be improved by using more parameters to describe the population and by introducing finite population corrections. Finally, we come back to recombination and show how this can be modelled.

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Author information

Authors and Affiliations

  1. Department of Electronics and Computer Science, University of Southampton, Southampton, SO17 1BJ, UK

    A. Prügel-Bennett & A. Rogers

Authors
  1. A. Prügel-Bennett
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  2. A. Rogers
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Editor information

Editors and Affiliations

  1. Ecole Polytechnique, CMAP, 91128, Palaiseau Cedex, France

    Leila Kallel

  2. Departement Wiskunde & Informatica, Universiteit Antwerpen (RUCA), Groenenborgerlaan 171, 2020, Antwerpen, Belgium

    Bart Naudts

  3. Department of Electronics and Computer Science Highfield, University of Southampton, SO17 1BJ, Southampton, UK

    Alex Rogers

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© 2001 Springer-Verlag Berlin Heidelberg

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Prügel-Bennett, A., Rogers, A. (2001). Modelling Genetic Algorithm Dynamics. In: Kallel, L., Naudts, B., Rogers, A. (eds) Theoretical Aspects of Evolutionary Computing. Natural Computing Series. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-04448-3_4

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  • DOI: https://doi.org/10.1007/978-3-662-04448-3_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-08676-2

  • Online ISBN: 978-3-662-04448-3

  • eBook Packages: Springer Book Archive

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