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On the mean convergence time of evolutionary algorithms without selection and mutation

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Parallel Problem Solving from Nature — PPSN III (PPSN 1994)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 866))

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Abstract

In this paper we study random genetic drift in a finite genetic population. Exact formulae for calculating the mean convergence time of the population are analytically derived and some results of numerical calculations are given. The calculations are compared to the results obtained in population genetics. A new proposition is derived for binary alleles and uniform crossover. Here the mean convergence time τ is almost proportional to the size of the population and to the logarithm of the number of the loci. The results of Monte Carlo type numerical simulations are in agreement with the results from the calculation.

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Author information

Author notes

  1. Hideki Asoh

    Present address: Electrotechnical Laboratory, Tsukuba, 305, Ibaraki, Japan

Authors and Affiliations

  1. German National Research Center for Computer Science (GMD), Schloss Birlinghoven, D-53754, Sankt Augustin, Germany

    Hideki Asoh & Heinz Mühlenbein

Authors
  1. Hideki Asoh
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  2. Heinz Mühlenbein
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Corresponding author

Correspondence to Hideki Asoh .

Editor information

Yuval Davidor Hans-Paul Schwefel Reinhard Männer

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© 1994 Springer-Verlag Berlin Heidelberg

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Asoh, H., Mühlenbein, H. (1994). On the mean convergence time of evolutionary algorithms without selection and mutation. In: Davidor, Y., Schwefel, HP., Männer, R. (eds) Parallel Problem Solving from Nature — PPSN III. PPSN 1994. Lecture Notes in Computer Science, vol 866. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-58484-6_253

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  • DOI: https://doi.org/10.1007/3-540-58484-6_253

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-58484-1

  • Online ISBN: 978-3-540-49001-2

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