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A New Model of Parallel Distributed Genetic Algorithms for Cluster Systems: Dual Individual DGAs

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High Performance Computing (ISHPC 2000)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1940))

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Abstract

A new model of parallel distributed genetic algorithm, Dual Individual Distributed Genetic Algorithm (DuDGA), is proposed. This algorithm frees the user from having to set some parameters because each island of Distributed Genetic Algorithm (DGA) has only two individuals. DuDGA can automatically determine crossover rate, migration rate, and island number. Moreover, compared to simple GA and DGA methods, DuDGA can find better solutions with fewer analyses. Capability and effectiveness of the DuDGA method are discussed using four typical numerical test functions.

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Author information

Authors and Affiliations

  1. Department of Knowledge Engineering and Computer Sciences, Doshisha University, 1-3 Tatara Miyakodani Kyotanabe Kyoto, 610-0321, Japan

    Tomoyuki Hiroyasu, Mitsunori Miki, Masahiro Hamasaki & Yusuke Tanimura

Authors
  1. Tomoyuki Hiroyasu
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  2. Mitsunori Miki
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  3. Masahiro Hamasaki
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  4. Yusuke Tanimura
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Editor information

Editors and Affiliations

  1. Departamento de Arquitectura de Computadores, Universidad Politecnica de Catalunya, Spain

    Mateo Valero

  2. Department of Information and Computer Sciences, Nara Women’s University, Japan

    Kazuki Joe

  3. Institute of Industrial Science Center for Conceptual Information Processing Research, University of Tokyo, Japan

    Masaru Kitsuregawa

  4. Graduate School of Engineering Electrical Engineering Department, University of Tokyo, Japan

    Hidehiko Tanaka

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© 2000 Springer-Verlag Berlin Heidelberg

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Hiroyasu, T., Miki, M., Hamasaki, M., Tanimura, Y. (2000). A New Model of Parallel Distributed Genetic Algorithms for Cluster Systems: Dual Individual DGAs. In: Valero, M., Joe, K., Kitsuregawa, M., Tanaka, H. (eds) High Performance Computing. ISHPC 2000. Lecture Notes in Computer Science, vol 1940. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-39999-2_36

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  • DOI: https://doi.org/10.1007/3-540-39999-2_36

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-41128-4

  • Online ISBN: 978-3-540-39999-5

  • eBook Packages: Springer Book Archive

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