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

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Learning and Intelligent Optimization (LION 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7997))

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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.

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References

  1. Deb, K.: Multi-Objective Optimization using Evolutionary Algorithms. Wiley, Chichester (2001)

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  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)

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  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)

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Author information

Authors and Affiliations

  1. Shinshu University, Matsumoto, Japan

    Hernán Aguirre & Kiyoshi Tanaka

  2. Université Lille 1, LIFL, UMR CNRS 8022, Lille, France

    Arnaud Liefooghe

  3. Université Nice Sophia-Antipolis, Nice, France

    Sébastien Verel

  4. Inria Lille-Nord Europe, Lille, France

    Arnaud Liefooghe & Sébastien Verel

Authors
  1. Hernán Aguirre
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  2. Arnaud Liefooghe
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  3. Sébastien Verel
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  4. Kiyoshi Tanaka
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Corresponding author

Correspondence to Hernán Aguirre .

Editor information

Editors and Affiliations

  1. Università Catania Dipto. Matematica e Informatica, Catania, Italy

    Giuseppe Nicosia

  2. Industrial & Systems Engineering, University of Florida, Gainesville, Florida, USA

    Panos Pardalos

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Aguirre, H., Liefooghe, A., Verel, S., Tanaka, K. (2013). Effects of Population Size on Selection and Scalability in Evolutionary Many-Objective Optimization. In: Nicosia, G., Pardalos, P. (eds) Learning and Intelligent Optimization. LION 2013. Lecture Notes in Computer Science(), vol 7997. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-44973-4_48

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  • DOI: https://doi.org/10.1007/978-3-642-44973-4_48

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-44972-7

  • Online ISBN: 978-3-642-44973-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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