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Optimization by Diploid Search Strategies

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Neural and Synergetic Computers

Part of the book series: Springer Series in Synergetics ((SSSYN,volume 42))

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Abstract

We present some results on optimization of cost functions using a population of parallel processors. Based on a simulated evolutionary search strategy diploid recombination is introduced as a means for maintaining variability in computational problems with large numbers of local extrema. The new strategy is compared to some traditional algorithms simulating evolution.

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Author information

Authors and Affiliations

  1. Institut für Theoretische Physik, Synergetik der Universität Stuttgart, Pfaffenwaldring 57/1V, D-7000, Stuttgart 80, Fed. Rep. of Germany

    W. Banzhaf

Authors
  1. W. Banzhaf
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Editor information

Editors and Affiliations

  1. Institut für Theoretische Physik und Synergetik, Universität Stuttgart, Pfaffenwaldring 57/IV, D-7000, Stuttgart 80, Fed. Rep. of Germany

    Hermann Haken

  2. Center for Complex Systems, Florida Atlantic University, 33431, Boca Raton, FL, USA

    Hermann Haken

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© 1988 Springer-Verlag Berlin Heidelberg

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Banzhaf, W. (1988). Optimization by Diploid Search Strategies. In: Haken, H. (eds) Neural and Synergetic Computers. Springer Series in Synergetics, vol 42. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-74119-7_11

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  • DOI: https://doi.org/10.1007/978-3-642-74119-7_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-74121-0

  • Online ISBN: 978-3-642-74119-7

  • eBook Packages: Springer Book Archive

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