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Cleaner fish optimization algorithm: a new bio-inspired meta-heuristic optimization algorithm

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Abstract

This paper proposes a new meta-heuristic optimization algorithm called Cleaner Fish Optimization algorithm (CFO) inspired by cleaner fish. The CFO simulates the movement behavior of cleaner fish when performing “cleaning services" and the behavior of female may change its sex to become a male, and defines two modes of position update. In addition, a two-generation cycle operation strategy is proposed to realize the optimization process. To verify the effectiveness of the CFO algorithm, 23 well-known CEC benchmark functions, CEC-2017 benchmark functions and 4 engineering design problems are adopted. Simulation results show that the proposed algorithm has a faster convergence rate and better optimal solution when it compared with several other meta-heuristic algorithms.

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Acknowledgements

The authors wish to acknowledge the National Natural Science Foundation of China (Grant No. U1731128); the Natural Science Foundation of Liaoning Province (Grant No. 2019-MS-174); the Foundation of Liaoning Province Education Administration (Grant No. LJKZ0279); the Team of Artificial Intelligence Theory and Application for the financial support.

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Authors and Affiliations

  1. School of Science, University of Science and Technology Liaoning, Anshan, 114051, Liaoning, China

    Wenya Zhang, Jian Zhao, Hao Liu & Liangping Tu

  2. Team of Artificial Intelligence Theory and Application, University of Science and Technology Liaoning, Anshan, 114051, Liaoning, China

    Jian Zhao, Hao Liu & Liangping Tu

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  1. Wenya Zhang
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  2. Jian Zhao
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  3. Hao Liu
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Contributions

The study is supported by all the authors. All authors contribute to the conception and design of the study. In the early stage of the study, the concept generation, material preparation and experimental ideas are completed by WZ and JZ. The method design, mathematical modeling and experimental data acquisition are completed by WZ, JZ, HL and LT. The analysis of experimental data, experimental design verification and visualization of experimental results are completed by WZ and JZ. The first draft of the thesis is completed by WZ. The review and revision of the paper have been guided by three teachers, JZ, HL and LT, and the final draft has been finalized. All authors have commented on previous manuscript editions. All authors read and approved the final manuscript.

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Correspondence to Jian Zhao.

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Zhang, W., Zhao, J., Liu, H. et al. Cleaner fish optimization algorithm: a new bio-inspired meta-heuristic optimization algorithm. J Supercomput (2024). https://doi.org/10.1007/s11227-024-06105-w

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