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A Hybrid Parallel Evolutionary Algorithm Based on Elite-Subspace Strategy and Space Transformation Search

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High Performance Computing and Applications

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

Abstract

In this paper, we present a new Hybrid Parallel Evolutionary Algorithm. It is based on Elite-subspace Strategy and combined with Space Transformation Search strategy to solve systems of non-linear equations. Verified by numerical experiments, our algorithm present an outstanding universal characteristics and superior convergence as well. All of the solutions can be obtained within a short period of time.

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Author information

Authors and Affiliations

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

    Xiaojian Dong, Song Yu & Zhijian Wu

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

    Zhangxing Chen

Authors
  1. Xiaojian Dong
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  2. Song Yu
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  3. Zhijian Wu
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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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Dong, X., Yu, S., Wu, Z., Chen, Z. (2010). A Hybrid Parallel Evolutionary Algorithm Based on Elite-Subspace Strategy and Space Transformation Search. 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_18

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  • DOI: https://doi.org/10.1007/978-3-642-11842-5_18

  • 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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