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Adaptive Objective Space Partitioning Using Conflict Information for Many-Objective Optimization

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Book cover Evolutionary Multi-Criterion Optimization (EMO 2011)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6576))

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Abstract

In a previous work we proposed a scheme for partitioning the objective space using the conflict information of the current Pareto front approximation found by an underlying multi-objective evolutionary algorithm. Since that scheme introduced additional parameters that have to be set by the user, in this paper we propose important modifications in order to automatically set those parameters. Such parameters control the number of solutions devoted to explore each objective subspace, and the number of generations to create a new partition. Our experimental results show that the new adaptive scheme performs as good as the non-adaptive scheme, and in some cases it outperforms the original scheme.

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Author information

Authors and Affiliations

  1. Computer Science Department, CINVESTAV-IPN, Mexico City, 07360, Mexico

    Antonio López Jaimes & Carlos A. Coello Coello

  2. Faculty of Engineering, Shinshu University, Nagano, 380-8553, Japan

    Hernán Aguirre & Kiyoshi Tanaka

Authors
  1. Antonio López Jaimes
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  2. Carlos A. Coello Coello
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  3. Hernán Aguirre
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  4. Kiyoshi Tanaka
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Editor information

Editors and Affiliations

  1. Department of Mathematics, Federal University of Minas Gerais, Av. Antônio Carlos 6627, 31270-901, Belo Horizonte, MG, Brazil

    Ricardo H. C. Takahashi

  2. Department of Mechanical Engineering, Indian Institute of Technology Kanpur, 208 016, Kanpur, India

    Kalyanmoy Deb

  3. Department of Computer Engineering, Centro Federal de Educaçao Tecnológica de Minas Gerais, Av. Amazonas 5253, 30421-169, Belo Horizonte, MG, Brazil

    Elizabeth F. Wanner

  4. Faculty of Economics, University of Catania, Corso Italia 55, 95129, Catania, Italy

    Salvatore Greco

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© 2011 Springer-Verlag Berlin Heidelberg

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López Jaimes, A., Coello Coello, C.A., Aguirre, H., Tanaka, K. (2011). Adaptive Objective Space Partitioning Using Conflict Information for Many-Objective Optimization. In: Takahashi, R.H.C., Deb, K., Wanner, E.F., Greco, S. (eds) Evolutionary Multi-Criterion Optimization. EMO 2011. Lecture Notes in Computer Science, vol 6576. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19893-9_11

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  • DOI: https://doi.org/10.1007/978-3-642-19893-9_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-19892-2

  • Online ISBN: 978-3-642-19893-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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