Hierarchical Chaotic Wingsuit Flying Search Algorithm with Balanced Exploitation and Exploration for Optimization

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  • LIU Sicheng
    Faculty of Engineering, University of Toyama
  • WANG Kaiyu
    Faculty of Engineering, University of Toyama
  • ZHENG Tao
    Faculty of Engineering, University of Toyama
  • YANG Haichuan
    Graduate School of Technology, Industrial and Social Sciences, Tokushima University
  • LEI Zhenyu
    Faculty of Engineering, University of Toyama
  • GAO Shangce
    Faculty of Engineering, University of Toyama
  • JIA Meng
    School of Computer Science and Engineering, Xi’an University of Technology

Bibliographic Information

Published
2025-02-01
Resource Type
journal article
DOI
  • 10.1587/transfun.2023eap1103
Publisher
The Institute of Electronics, Information and Communication Engineers

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<p>Wingsuit flying search is a meta-heuristic algorithm that effectively searches for optimal solutions by narrowing down the search space iteratively. However, its performance is affected by the balance between exploration and exploitation. We propose a four-layered hierarchical population structure algorithm, multi-layered chaotic wingsuit flying search (MCWFS), to promote such balance in this paper. The proposed algorithm consists of memory, elite, sub-elite, and population layers. Communication between the memory and elite layers enhances exploration ability while maintaining population diversity. The information flow from the population layer to the elite layer ensures effective exploitation. We evaluate the performance of the proposed MCWFS algorithm by conducting comparative experiments on IEEE Congress on Evolutionary Computation (CEC) benchmark functions. Experimental results prove that MCWFS is superior to the original algorithm in terms of solution quality and search performance. Compared with other representative algorithms, MCWFS obtains more competitive results on composite problems and real-world problems.</p>

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