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A Hybrid Particle Swarm Optimization Algorithm Based on Space Transformation Search and a Modified Velocity Model

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High Performance Computing and Applications

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5938))

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Abstract

Particle Swarm Optimization (PSO) has shown its fast search speed in many complicated optimization and search problems. However, PSO often easily falls into local optima because the particles would quickly get closer to the best particle. Under these circumstances, the best particle could hardly be improved. This paper proposes a new hybrid PSO (HPSO) to solve this problem by combining space transformation search (STS) with a new modified velocity model. Experimental studies on 8 benchmark functions demonstrate that the HPSO holds good performance in solving both unimodal and multimodal functions optimization problems.

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Authors and Affiliations

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

    Song Yu, Zhijian Wu & Hui Wang

  2. Department of Chemical and Petroleum Engineering, Schulich School of Engineering, University of Calgary, Calgary, 2500, Canada

    Zhangxing Chen

Authors
  1. Song Yu
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  2. Zhijian Wu
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  3. Hui Wang
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  4. Zhangxing Chen
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Editor information

Editors and Affiliations

  1. School of Computer Engineering and Science, Shanghai University, 200072, Shanghai, P.R. China

    Wu Zhang  & Weiqin Tong  & 

  2. Schulich School of Engineering, University of Calgary, T2N 1N4, Calgary, AB, Canada

    Zhangxin Chen

  3. Department of Mathematics, University of Wyoming, 1000 University Avenue, 82071-3036, Laramie, WY, USA

    Craig C. Douglas

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© 2010 Springer-Verlag Berlin Heidelberg

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Yu, S., Wu, Z., Wang, H., Chen, Z. (2010). A Hybrid Particle Swarm Optimization Algorithm Based on Space Transformation Search and a Modified Velocity Model. In: Zhang, W., Chen, Z., Douglas, C.C., Tong, W. (eds) High Performance Computing and Applications. Lecture Notes in Computer Science, vol 5938. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11842-5_73

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  • DOI: https://doi.org/10.1007/978-3-642-11842-5_73

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-11841-8

  • Online ISBN: 978-3-642-11842-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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