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Corner Based Many-Objective Optimization

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Nature Inspired Cooperative Strategies for Optimization (NICSO 2013)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 512))

Abstract

The performance of multi-objective evolutionary algorithms (MOEA) is severely deteriorated when applied to many-objective problems. For Pareto dominance based techniques, available information about optimal solutions can be used to improve their performance. This is the case of corner solutions. This work considers the behaviour of three multi-objective algorithms (NSGA-II, SMPSO and GDE3) when corner solutions are inserted into the population at different evolutionary stages. Corner solutions are found using specific algorithms. Preliminary results are presented concerning the behaviour of the aforementioned algorithms in five benchmark problems (DTLZ1-5).

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Authors and Affiliations

  1. Department of Engineering, School of Sciences and Technology, INESC TEC - INESC Technology and Science (formerly INESC Porto, UTAD pole), 5001-801, Vila Real, Portugal

    Hélio Freire, P. B. de Moura Oliveira, E. J. Solteiro Pires & Maximino Bessa

Authors
  1. Hélio Freire
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  2. P. B. de Moura Oliveira
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  3. E. J. Solteiro Pires
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  4. Maximino Bessa
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Corresponding author

Correspondence to Hélio Freire .

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Editors and Affiliations

  1. School of Computer Science, University of Nottingham, Nottingham, United Kingdom

    German Terrazas

  2. School of Computing, University of Kent, Canterbury, Kent, United Kingdom

    Fernando E. B. Otero

  3. Center for Research on ICT, University of Granada, Granada, Spain

    Antonio D. Masegosa

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Freire, H., de Moura Oliveira, P.B., Solteiro Pires, E.J., Bessa, M. (2014). Corner Based Many-Objective Optimization. In: Terrazas, G., Otero, F., Masegosa, A. (eds) Nature Inspired Cooperative Strategies for Optimization (NICSO 2013). Studies in Computational Intelligence, vol 512. Springer, Cham. https://doi.org/10.1007/978-3-319-01692-4_10

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  • DOI: https://doi.org/10.1007/978-3-319-01692-4_10

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-01691-7

  • Online ISBN: 978-3-319-01692-4

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