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Constrained Optimization by ε Constrained Particle Swarm Optimizer with ε-level Control

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Soft Computing as Transdisciplinary Science and Technology

Part of the book series: Advances in Soft Computing ((AINSC,volume 29))

Summary

In this study, ε constrained particle swarm optimizer εPSO, which is the combination of the ε constrained method and particle swarm optimization, is proposed to solve constrained optimization problems. The ε constrained methods can convert algorithms for unconstrained problems to algorithms for constrained problems using the ε level comparison, which compares the search points based on the constraint violation of them. In the ε PSO, the agents who satisfy the constraints move to optimize the objective function and the agents who don’t satisfy the constraints move to satisfy the constraints. Also, the way of controlling ε-level is given to solve problems with equality constraints. The effectiveness of the ε PSO is shown by comparing the ε PSO with GENOCOP5.0 on some nonlinear constrained problems with equality constraints.

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Author information

Authors and Affiliations

  1. Department of Intelligent Systems, Hiroshima City University, Asaminami-ku, Hiroshima, 731-3194, Japan

    Tetsuyuki Takahama

  2. Faculty of Commercial Sciences, Hiroshima Shudo University, Asaminami-ku, Hiroshima, 731-3195, Japan

    Setsuko Sakai

Authors
  1. Tetsuyuki Takahama
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  2. Setsuko Sakai
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Editor information

Editors and Affiliations

  1. Dept. of Computer Science, Oklahoma State University, North Greenwood Avenue 700, 74106, Tulsa, USA

    Ajith Abraham

  2. Dept. of Computer Science and Systems Engineering, Muroran Institute of Technology, Mizumoto-cho 27-1, 050-8585, Muroran, Hokkaido, Japan

    Yasuhiko Dote

  3. Dept. of Computational Science and Engineering, Nagoya University, Furo-cho, Chikusa-ku, 464-8601, Nagoya, Aichi-ken, Japan

    Takeshi Furuhashi

  4. Institut für Sicherheits-/Prüftechnik, Fraunhofer IPK Berlin, Pascalstr. 8-9, 10587, Berlin, Germany

    Mario Köppen

  5. Division of Complex Systems Technology Graduate School of Engineering, University of Hokkaido, N-13, W-8 060 KITA-KU, Sapporo, Japan

    Azuma Ohuchi

  6. PRESTO Japan Science & Technology Corp. GSSM, University of Tsukuba, 3-29-1 Otsuka, Bunkyo-ku, 12-0012, Tokyo, Japan

    Yukio Ohsawa

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© 2005 Springer-Verlag Berlin Heidelberg

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Takahama, T., Sakai, S. (2005). Constrained Optimization by ε Constrained Particle Swarm Optimizer with ε-level Control. In: Abraham, A., Dote, Y., Furuhashi, T., Köppen, M., Ohuchi, A., Ohsawa, Y. (eds) Soft Computing as Transdisciplinary Science and Technology. Advances in Soft Computing, vol 29. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32391-0_105

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  • DOI: https://doi.org/10.1007/3-540-32391-0_105

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25055-5

  • Online ISBN: 978-3-540-32391-4

  • eBook Packages: EngineeringEngineering (R0)

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