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Preserving Diversity through Diploidy and Meiosis for Improved Genetic Algorithm Performance in Dynamic Environments

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Advances in Information Systems (ADVIS 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2457))

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Abstract

Genetic algorithms have been applied to a diverse field of problems with promising results. Using genetic algorithms modified to various degrees for tackling dynamic problems has attracted much attention in recent years. The main reason classical genetic algorithms do not perform well in such problems is that they converge and lose their genetic diversity. However, to be able to adapt to a change in the environment, diversity must be maintained in the gene pool of the population. One approach to the problem involves a diploid representation of individuals. Using this representation with a dynamic dominance map mechanism and meiotic cell division helps preserve diversity. In this paper, the effects of using diploidy and meiosis with such a dominance mechanism are explored. Experiments are carried out using a variation of the 0-1 knapsack problem as a testbed to determine the effects of the different aspects of the approach on population diversity and performance. The results obtained show promising enhancements.

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Author information

Authors and Affiliations

  1. Istanbul Technical University, 80626, Istanbul, Turkey

    A. Sima Etaner-Uyar

  2. Istanbul Technical University, 80626, Istanbul, Turkey

    A. Emre Harmanci

Authors
  1. A. Sima Etaner-Uyar
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  2. A. Emre Harmanci
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Editor information

Editors and Affiliations

  1. Computer Engineering Department, Dokuz Eylul University, 35100, Izmir, Bornova, Turkey

    Tatyana Yakhno

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© 2002 Springer-Verlag Berlin Heidelberg

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Etaner-Uyar, A.S., Harmanci, A.E. (2002). Preserving Diversity through Diploidy and Meiosis for Improved Genetic Algorithm Performance in Dynamic Environments. In: Yakhno, T. (eds) Advances in Information Systems. ADVIS 2002. Lecture Notes in Computer Science, vol 2457. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36077-8_32

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  • DOI: https://doi.org/10.1007/3-540-36077-8_32

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-00009-9

  • Online ISBN: 978-3-540-36077-3

  • eBook Packages: Springer Book Archive

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