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Adaptive Particle Swarm Optimization via Velocity Feedback

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Soft Computing as Transdisciplinary Science and Technology

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

Summary

This paper describes an adaptive strategy for tuning the parameters of the PSO method based on an analysis of the dynamics of PSO. This adaptive tuning strategy is based on the results of an analysis of the dynamics of average velocity of the particles with successful search processes. The feasibility and advantages of the proposed adaptive PSO method are demonstrated through numerical simulations using a typical global optimization test problem.

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References

  1. J. Kennedy and R. C. Eberhart (2001) “Swarm Interlligence”, Morgan Kaufmann Publishers.

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  2. M. Clerc and J. Kennedy (2002) “The Particle Swarm-Explosion, Stability, and Convergence in a Multidimensional Complex Space”, IEEE Transactions on Evolutionary Computation, Vol.6, No.1, pp.58–73.

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  3. Keiichiro Yasuda and Nobuhiro Iwasaki (Oct.2004) “Adaptive Particle Swarm Optimization using velocity information of swarm”, IEEE International Conference on Systems, Man & Cybernetics Proceedings, pp.3475–3481.

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Author information

Authors and Affiliations

  1. Department of Electrical Engineering, Tokyo Metropolitan University, 1-1, Minamiosawa, Hachioji-shi, Tokyo, 192-0397, Japan

    Keiichiro Yasuda & Nobuhiro Iwasaki

Authors
  1. Keiichiro Yasuda
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  2. Nobuhiro Iwasaki
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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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Yasuda, K., Iwasaki, N. (2005). Adaptive Particle Swarm Optimization via Velocity Feedback. 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_49

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  • DOI: https://doi.org/10.1007/3-540-32391-0_49

  • 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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