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A Communication Strategy for Paralleling Grey Wolf Optimizer

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Genetic and Evolutionary Computing (GEC 2015)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 388))

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  • International Conference on Genetic and Evolutionary Computing

Abstract

In this paper, a communication strategy for the parallelized Grey Wolf Optimizer is proposed for solving numerical optimization problems. In this proposed method, the population wolves are split into several independent groups based on the original structure of the Grey Wolf Optimizer (GWO), and the proposed communication strategy provides the information flow for the wolves to communicate in different groups. Four benchmark functions are used to test the behavior of convergence, the accuracy, and the speed of the proposed method. According to the experimental results, the proposed communicational strategy increases the speed and accuracy of the GWO on finding the best solution is up to 75% and 45% respectively in comparison with original method.

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Author information

Authors and Affiliations

  1. Department of Electronics Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, Taiwan

    Tien-Szu Pan, Thi-Kien Dao & Trong-The Nguyen

  2. School of Computer Science, Engineering and Mathematics, Flinders University, Adelaide, Australia

    Shu-Chuan Chu

Authors
  1. Tien-Szu Pan
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  2. Thi-Kien Dao
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  3. Trong-The Nguyen
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  4. Shu-Chuan Chu
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Corresponding author

Correspondence to Thi-Kien Dao .

Editor information

Editors and Affiliations

  1. Faculty of Engineering, University of Miyazaki, Miyazaki, Japan

    Thi Thi Zin

  2. School of Computer Science and Tech..., Harbin Institute of Technology, Shenzhen Graduate School , Shenzhen, China

    Jerry Chun-Wei Lin

  3. College of Information Science and Engg, Fujian University of Technology, Fuzhou, China

    Jeng-Shyang Pan

  4. Faculty of Engineering, University of Miyazaki, Miyazaki, Japan

    Pyke Tin

  5. Faculty of Engineering, University of Miyazaki, Miyazaki, Japan

    Mitsuhiro Yokota

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© 2016 Springer International Publishing Switzerland

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Pan, TS., Dao, TK., Nguyen, TT., Chu, SC. (2016). A Communication Strategy for Paralleling Grey Wolf Optimizer. In: Zin, T., Lin, JW., Pan, JS., Tin, P., Yokota, M. (eds) Genetic and Evolutionary Computing. GEC 2015. Advances in Intelligent Systems and Computing, vol 388. Springer, Cham. https://doi.org/10.1007/978-3-319-23207-2_25

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  • DOI: https://doi.org/10.1007/978-3-319-23207-2_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23206-5

  • Online ISBN: 978-3-319-23207-2

  • eBook Packages: EngineeringEngineering (R0)

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