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Generalization of Dominance Relation-Based Replacement Rules for Memetic EMO Algorithms

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Genetic and Evolutionary Computation — GECCO 2003 (GECCO 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2723))

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Abstract

In this paper, we generalize the replacement rules based on the dominance relation in multiobjective optimization. Ordinary two replacement rules based on the dominance relation are usually employed in a local search (LS) for multiobjective optimization. One is to replace a current solution with a solution which dominates it. The other is to replace the solution with a solution which is not dominated by it. The movable area in the LS with the first rule is very small when the number of objectives is large. On the other hand, it is too huge to move efficiently with the latter. We generalize these extreme rules by counting the number of improved objectives in a candidate solution for LS. We propose a LS with the generalized replacement rule for existing EMO algorithms. Its effectiveness is shown on knapsack problems with two, three, and four objectives.

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Author information

Authors and Affiliations

  1. Department of Informatics, Kansai University, 2-1-1 Ryozenji-cho, Takatsuki, Osaka, 569-1095, Japan

    Tadahiko Murata

  2. Department of Industrial Engineering, Osaka Prefecture University, 1-1 Gakuen-cho, Sakai, Osaka, 599-8531, Japan

    Shiori Kaige & Hisao Ishibuchi

Authors
  1. Tadahiko Murata
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  2. Shiori Kaige
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  3. Hisao Ishibuchi
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Editor information

Editors and Affiliations

  1. Lawrence Livermore National Laboratory, Center for Applied Scientific Computing (CASC), 7000 East Avenue, L-561, Livermore, CA, 94550, USA

    Erick Cantú-Paz

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© 2003 Springer-Verlag Berlin Heidelberg

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Murata, T., Kaige, S., Ishibuchi, H. (2003). Generalization of Dominance Relation-Based Replacement Rules for Memetic EMO Algorithms. In: Cantú-Paz, E., et al. Genetic and Evolutionary Computation — GECCO 2003. GECCO 2003. Lecture Notes in Computer Science, vol 2723. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45105-6_130

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  • DOI: https://doi.org/10.1007/3-540-45105-6_130

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40602-0

  • Online ISBN: 978-3-540-45105-1

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