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A New Dynamic Particle Swarm Optimizer

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Book cover Simulated Evolution and Learning (SEAL 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4247))

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Abstract

This paper presents a new optimization model— Dynamic Particle Swarm Optimizer (DPSO). A new acceptance rule that based on the principle of minimal free energy from the statistical mechanics is introduced to the standard particle swarm optimizer. A definition of the entropy of the particle system is given. Then the law of entropy increment is applied to control the algorithm. Simulations have been done to illustrate the significant and effective impact of this new rule on the particle swarm optimizer.

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Author information

Authors and Affiliations

  1. State Key Lab. of Software Engineering, Wuhan University, Wuhan, 430072, China

    Binbin Zheng, Yuanxiang Li & Xianjun Shen

  2. College of Computer Science, South-Central University For Nationalities, Wuhan, 430074, China

    Bojin Zheng

Authors
  1. Binbin Zheng
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  2. Yuanxiang Li
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  3. Xianjun Shen
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  4. Bojin Zheng
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Editor information

Editors and Affiliations

  1. Department of Industrial Engineering and Management, Cheng Shiu University, Kaohsiung County Taiwan, ROC

    Tzai-Der Wang

  2. School of Computer Science and information Technology, RMIT University, VIC 3001, Melbourne, Australia

    Xiaodong Li

  3. AI-ECON Research Center, Department of Economics, National Chengchi University, 11623, Taipei, Taiwan

    Shu-Heng Chen

  4. Department of Computer Science and Technology, University of Sci. & Tech. of China, 230026, Hefei, Anhui, P.R. China

    Xufa Wang

  5. School of Information Technology and Electrical Engineering, University of New South Wales, Australian Defence Force Academy, Canberra, Australia

    Hussein Abbass

  6. The Univertity of Tokyo, Japan

    Hitoshi Iba

  7. Department of Computer, University of Science and Technology of China, 230027, Hefei, China

    Guo-Liang Chen

  8. University of Birmingham, Birmingham, UK

    Xin Yao

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© 2006 Springer-Verlag Berlin Heidelberg

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Cite this paper

Zheng, B., Li, Y., Shen, X., Zheng, B. (2006). A New Dynamic Particle Swarm Optimizer. In: Wang, TD., et al. Simulated Evolution and Learning. SEAL 2006. Lecture Notes in Computer Science, vol 4247. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11903697_61

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  • DOI: https://doi.org/10.1007/11903697_61

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-47331-2

  • Online ISBN: 978-3-540-47332-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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