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Hybrid remora crayfish optimization for engineering and wireless sensor network coverage optimization

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Abstract

This paper proposes a novel hybrid metaheuristic algorithm called the remora crayfish optimization algorithm (HRCOA) designed for solving continuous optimization problems. The crayfish optimization algorithm (COA), recently proposed as a meta-heuristic algorithm (MA), exhibits certain limitations such as imbalanced exploration and exploitation capacities, susceptibility to premature optimization, and a propensity for stagnation. To address these shortcomings, we incorporate the exploitation operators from the remora optimization algorithm (ROA) to enhance the exploitative behaviors of COA. In addition, we simplify the summer resort operator in the original COA to streamline the search operator design, thus avoiding unnecessary complexity. Furthermore, numerical experiments on 10-dimensional (D) and 20-D CEC2022 benchmark functions, 50-D and 100-D CEC2020 benchmark functions, engineering optimization problems, and wireless sensor networks (WSNs) coverage optimization problems are conducted to investigate the performance of our proposed HRCOA comprehensively. We compare the proposed HRCOA against eight well-known state-of-the-art MAs, including CMAES and the original COA, as competitor algorithms. The experimental and statistical results confirm the effectiveness, competitiveness, and scalability of our proposal. Finally, we conclude that the proposed HRCOA possesses significant potential for addressing diverse optimization challenges in real-world scenarios.

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The source code of this research can be downloaded from https://github.com/RuiZhong961230/HRCOA.

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Acknowledgements

This work was supported by JST SPRING Grant Number JPMJSP2119.

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Authors and Affiliations

  1. Graduate School of Information Science and Technology, Hokkaido University, Sapporo, Japan

    Rui Zhong

  2. Logistics Research Center, Shanghai Maritime University, Shanghai, China

    Qinqin Fan

  3. Department of Engineering, University of Fukui, Fukui, Japan

    Chao Zhang

  4. Institute of Science and Technology, Niigata University, Niigata, Japan

    Jun Yu

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  1. Rui Zhong
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  2. Qinqin Fan
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  3. Chao Zhang
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  4. Jun Yu
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RZ: conceptualization, methodology, investigation, writing—original draft, writing—review & editing, and funding acquisition. QF: investigation, methodology, formal analysis, and writing—review & editing. CZ: conceptualization and writing—review & editing. JY: writing—review & editing, and project administration.

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Correspondence to Jun Yu.

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Zhong, R., Fan, Q., Zhang, C. et al. Hybrid remora crayfish optimization for engineering and wireless sensor network coverage optimization. Cluster Comput (2024). https://doi.org/10.1007/s10586-024-04508-1

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