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Binary Chimp Optimization Algorithm (BChOA): a New Binary Meta-heuristic for Solving Optimization Problems

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Abstract

Chimp optimization algorithm (ChOA) is a newly proposed meta-heuristic algorithm inspired by chimps’ individual intelligence and sexual motivation in their group hunting. The preferable performance of ChOA has been approved among other well-known meta-heuristic algorithms. However, its continuous nature makes it unsuitable for solving binary problems. Therefore, this paper proposes a novel binary version of ChOA and attempts to prove that the transfer function is the most important part of binary algorithms. Therefore, four S-shaped and V-shaped transfer functions, as well as a novel binary approach, have been utilized to investigate the efficiency of binary ChOAs (BChOA) in terms of convergence speed and local minima avoidance. In this regard, forty-three unimodal, multimodal, and composite optimization functions and ten IEEE CEC06-2019 benchmark functions were utilized to evaluate the efficiency of BChOAs. Furthermore, to validate the performance of BChOAs, four newly proposed binary optimization algorithms were compared with eighteen novel state-of-the-art algorithms. The results indicate that both the novel binary approach and V-shaped transfer functions improve the efficiency of BChOAs in a statistically significant way.

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Authors and Affiliations

  1. Shenma Cord Fabric Development Co., Ltd, Henan, Pingdingshan, 467000, China

    Jianhao Wang

  2. Department of Electrical Engineering, Imam Khomeini Marine Science University, 46517-83311, Nowshahr, Iran

    Mohammad Khishe & Hassan Mohammadi

  3. Department of Geodesy and Geomatics, K. N. Toosi University of Technology, 19967-15433, Tehran, Iran

    Mehrdad Kaveh

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  1. Jianhao Wang
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Contributions

This work was carried out in close collaboration among all authors. J. Wang contributed to the data analysis, interpretation, and critical revision of the paper. M. Khishe conceived the method and experiments and implemented and conducted the experiments. M. Kaveh contributed to the experiments and in analyzing the results. H. Mohammadi analyzed the results. All the authors have contributed to writing the paper.

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Correspondence to Mohammad Khishe.

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Wang, J., Khishe, M., Kaveh, M. et al. Binary Chimp Optimization Algorithm (BChOA): a New Binary Meta-heuristic for Solving Optimization Problems. Cogn Comput 13, 1297–1316 (2021). https://doi.org/10.1007/s12559-021-09933-7

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