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International Conference on Artificial Intelligence and Soft Computing

ICAISC 2006: Artificial Intelligence and Soft Computing – ICAISC 2006 pp 430–439Cite as

Improved Multi-Objective Diversity Control Oriented Genetic Algorithm

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4029))

Abstract

This paper presents an improved multi-objective diversity control oriented genetic algorithm (MODCGA-II). The improvement includes the introduction of an objective-domain diversity control operator, which is chromosome representation independent, and a solution archive. The performance comparison between the MODCGA-II, a non-dominated sorting genetic algorithm II (NSGA-II) and an improved strength Pareto evolutionary algorithm (SPEA-II) is carried out where different two-objective benchmark problems with specific multi-objective characteristics are utilised. The results indicate that the MODCGA-II solutions are better than the solutions generated by the NSGA-II and SPEA-II in terms of the closeness to the true Pareto optimal solutions and the uniformity of solution distribution along the Pareto front.

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Author information

Authors and Affiliations

  1. Department of Production Engineering, King Mongkut’s Institute of Technology North Bangkok, 1518 Piboolsongkram Road, Bangsue, Bangkok, 10800, Thailand

    Theera Piroonratana

  2. Research and Development Center for Intelligent Systems, King Mongkut’s Institute of Technology North Bangkok, 1518 Piboolsongkram Road, Bangsue, Bangkok, 10800, Thailand

    Nachol Chaiyaratana

Authors
  1. Theera Piroonratana
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  2. Nachol Chaiyaratana
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Editor information

Editors and Affiliations

  1. Department of Artificial Intelligence, Academy of Humanities and Economics, Poland

    Leszek Rutkowski

  2. Institute of Automatics, AGH University of Science and Technology, Al. Mickiewicza 30, PL-30-059, Kraków, Poland

    Ryszard Tadeusiewicz

  3. Department of Electrical Engineering and Computer Sciences, Berkeley Initiative in Soft Computing (BISC), University of California, 94720-1776, Berkeley, CA, USA

    Lotfi A. Zadeh

  4. Department of Electrical Engineering, University of Louisville, 40292, Louisville, KY, U.S.A

    Jacek M. Żurada

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© 2006 Springer-Verlag Berlin Heidelberg

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Piroonratana, T., Chaiyaratana, N. (2006). Improved Multi-Objective Diversity Control Oriented Genetic Algorithm. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Żurada, J.M. (eds) Artificial Intelligence and Soft Computing – ICAISC 2006. ICAISC 2006. Lecture Notes in Computer Science(), vol 4029. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11785231_46

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  • DOI: https://doi.org/10.1007/11785231_46

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-35748-3

  • Online ISBN: 978-3-540-35750-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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