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Supporting polyploidy in genetic algorithms using dominance vectors

  • Enhanced Evolutionary Operators
  • Conference paper
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Evolutionary Programming VI (EP 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1213))

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Abstract

By memorizing alleles that have been successful in the past, polyploidy has been found to be beneficial for adapting to changing environments. This paper explores the benefits of using polyploidy in Genetic Algorithms. Polyploidy is provided in our approach by using a local chromosome to reflect dominance in diploid and tetraploid organisms, with and without evolving crossover points, added to provide linkage between chromosomes and the dominance control vector. We compare our polyploid approach to a haploid implementation for a benchmark that involves a 0/1 knapsack problem with time varying weight constraints.

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Authors and Affiliations

  1. Department of Computer Science, University of Houston, 77204-3475, Houston, TX

    Ben S. Hadad & Christoph F. Eick

Authors
  1. Ben S. Hadad
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  2. Christoph F. Eick
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Editor information

Peter J. Angeline Robert G. Reynolds John R. McDonnell Russ Eberhart

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© 1997 Springer-Verlag Berlin Heidelberg

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Hadad, B.S., Eick, C.F. (1997). Supporting polyploidy in genetic algorithms using dominance vectors. In: Angeline, P.J., Reynolds, R.G., McDonnell, J.R., Eberhart, R. (eds) Evolutionary Programming VI. EP 1997. Lecture Notes in Computer Science, vol 1213. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0014814

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  • DOI: https://doi.org/10.1007/BFb0014814

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-62788-3

  • Online ISBN: 978-3-540-68518-0

  • eBook Packages: Springer Book Archive

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