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A Hybrid Parallel Algorithm With Multiple Improved Strategies

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Intelligent Information Processing XI (IIP 2022)

Part of the book series: IFIP Advances in Information and Communication Technology ((IFIPAICT,volume 643))

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Abstract

This paper proposes a novel hybrid parallel algorithm with multiple improved strategies. The whole population is divided into three subpopulations and each sub-population executes butterfly optimization algorithm, grey wolf optimization algorithm, and marine predator algorithm respectively. Meanwhile, they share information through three different communication strategies. And in order to improve the performance of the algorithm, the text uses the cubic chaotic mapping mechanism in the initialization stage. At the same time, the idea of adaptive parameter strategy is also introduced, so that some hyperparameters are changed along with the iteration. The results show that the algorithm can provide very competitive results, and is superior to the best algorithm in the literature on most test functions.

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Author information

Authors and Affiliations

  1. College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, China

    Tingting Wang, Jeng-Shyang Pan, Pei-Cheng Song & Shu-Chuan Chu

  2. Department of Information Management, Chaoyang University of Technology, Taichung, Taiwan

    Jeng-Shyang Pan

  3. College of Science and Engineering, Flinders University, Bedford Park, Australia

    Shu-Chuan Chu

Authors
  1. Tingting Wang
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  2. Jeng-Shyang Pan
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  3. Pei-Cheng Song
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  4. Shu-Chuan Chu
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Corresponding author

Correspondence to Shu-Chuan Chu .

Editor information

Editors and Affiliations

  1. Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China

    Zhongzhi Shi

  2. IRD, Sorbonne University, Bondy, France

    Jean-Daniel Zucker

  3. Nanyang Technological University, Singapore, Singapore

    Bo An

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Wang, T., Pan, JS., Song, PC., Chu, SC. (2022). A Hybrid Parallel Algorithm With Multiple Improved Strategies. In: Shi, Z., Zucker, JD., An, B. (eds) Intelligent Information Processing XI. IIP 2022. IFIP Advances in Information and Communication Technology, vol 643. Springer, Cham. https://doi.org/10.1007/978-3-031-03948-5_19

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  • DOI: https://doi.org/10.1007/978-3-031-03948-5_19

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-03947-8

  • Online ISBN: 978-3-031-03948-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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