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International Conference on Parallel Problem Solving from Nature

PPSN 1994: Parallel Problem Solving from Nature — PPSN III pp 36–45Cite as

A diploid genetic algorithm for preserving population diversity — Pseudo-Meiosis GA

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

Abstract

This paper proposes a diploid genetic algorithm, which is named the pseudo-Meiosis Genetic Algorithm (psM GA), that preserves population diversity. The psM GA has a meiosis-like procedure to generate a phenotype from a pair of functionally different chromosomes, unlike a conventional diploid GA with dominance. Another new feature is a procedure for re-pairing two chromosomes for the next generation. The psM GA is applied to a non-stationary traveling salesman problem (TSP), which conventional diploid GAs can hardly cope with. The psM GA preserved population diversity and adapted the population quickly to the problem changes.

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Author information

Authors and Affiliations

  1. Fujitsu Laboratories Ltd., Institute for Social Information Science, 9-3, Nakase 1-chome, Mihama-ku, Chiba-shi, 261, Chiba, Japan

    Yoshida Yukiko & Adachi Nobue

Authors
  1. Yoshida Yukiko
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  2. Adachi Nobue
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Editor information

Yuval Davidor Hans-Paul Schwefel Reinhard Männer

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© 1994 Springer-Verlag Berlin Heidelberg

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Yukiko, Y., Nobue, A. (1994). A diploid genetic algorithm for preserving population diversity — Pseudo-Meiosis GA. 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_248

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  • DOI: https://doi.org/10.1007/3-540-58484-6_248

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-58484-1

  • Online ISBN: 978-3-540-49001-2

  • eBook Packages: Springer Book Archive

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