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International Conference on Evolutionary Multi-Criterion Optimization

EMO 2013: Evolutionary Multi-Criterion Optimization pp 276–290Cite as

Effect of Dominance Balance in Many-Objective Optimization

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7811))

Abstract

This paper examines the effect of dominance balance in many-objective optimization. The dominance balance can be defined by the ratio of the dominating space to the objective space. Here, CDAS, which is one of the most powerful evolutionary many-objective optimization algorithms, is known to be able to change the ratio of the dominating space by relaxing the definition of Pareto dominance with its user-specified parameter. However, the dominance balance is too difficult to control for the parameter in the higher-dimensional objective space. Therefore, we analyze the performance of CDAS by changing the ratio of the dominating space directly in even steps from the minimum to the maximum according to the number of objectives. The corresponding user-specified parameter in CDAS can be obtained from an equation which we assume in the paper. As benchmark test problems, we use DTLZ1, DTLZ2, DTLZ3, and DTLZ4 with two to ten objectives. From computational experiments, we can conclude that the optimal ratio of the dominating space differs depending on the problem at hand. It can be also said that the performance of CDAS is good especially when the ratio of the dominating space is small enough but not the minimum. Based on these observations, we propose a new version of CDAS called CDAS-D which controls the ratio of the dominating space dynamically during optimization.

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Author information

Authors and Affiliations

  1. Honda Research Institute Europe GmbH, Carl-Legien-Strasse 30, 63073, Offenbach am Main, Germany

    Kaname Narukawa

Authors
  1. Kaname Narukawa
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Editor information

Editors and Affiliations

  1. Department of Automatic Control and Systems Engineering, University of Sheffield, Mappin Street, S1 3JD, Sheffield, UK

    Robin C. Purshouse

  2. Department of Automatic Control Systems and Engineering, University of Sheffield, Mappin Street, S1 3JD, Sheffield, UK

    Peter J. Fleming

  3. Department of Informatics Engineering, University of Coimbra, Pólo II, Pinhal de Marrocos, 3030-290, Coimbra, Portugal

    Carlos M. Fonseca

  4. Department of Economics and Business, University of Catania, Corso Italia 55, 95129, Catania, Italy

    Salvatore Greco

  5. Unilever Research & Development Port Sunlight, Quarry Road East, CH63 3JW, Merseyside, UK

    Jane Shaw

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© 2013 Springer-Verlag Berlin Heidelberg

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Narukawa, K. (2013). Effect of Dominance Balance in Many-Objective Optimization. In: Purshouse, R.C., Fleming, P.J., Fonseca, C.M., Greco, S., Shaw, J. (eds) Evolutionary Multi-Criterion Optimization. EMO 2013. Lecture Notes in Computer Science, vol 7811. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37140-0_23

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  • DOI: https://doi.org/10.1007/978-3-642-37140-0_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37139-4

  • Online ISBN: 978-3-642-37140-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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