Effects of Population Size on Selection and Scalability in Evolutionary Many-Objective Optimization

  • Hernán Aguirre
  • Arnaud Liefooghe
  • Sébastien Verel
  • Kiyoshi Tanaka
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7997)

Abstract

In this work we study population size as a fraction of the true Pareto optimal set and analyze its effects on selection and performance scalability of a conventional multi-objective evolutionary algorithm applied to many-objective optimization of small MNK-landscapes.

References

  1. 1.
    Deb, K.: Multi-Objective Optimization using Evolutionary Algorithms. Wiley, Chichester (2001)Google Scholar
  2. 2.
    Ishibuchi, H., Tsukamoto, N., Nojima, Y.: Evolutionary many-objective optimization: a short review. In: Proceedings of IEEE Congress on Evolutionary Computation (CEC 2008), pp. 2424–2431. IEEE Press (2008)Google Scholar
  3. 3.
    Aguirre, H., Tanaka, K.: Insights on properties of multi-objective MNK-landscapes. In: Proceedings of 2004 IEEE Congress on Evolutionary Computation, pp. 196–203. IEEE Service Center (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Hernán Aguirre
    • 1
  • Arnaud Liefooghe
    • 2
    • 4
  • Sébastien Verel
    • 3
    • 4
  • Kiyoshi Tanaka
    • 1
  1. 1.Shinshu UniversityMatsumotoJapan
  2. 2.Université Lille 1, LIFL, UMR CNRS 8022LilleFrance
  3. 3.Université Nice Sophia-AntipolisNiceFrance
  4. 4.Inria Lille-Nord EuropeLilleFrance

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