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An Improved Honey Badger Algorithm through Fusing Multi-Strategies

Zhiwei Ye1, Tao Zhao1, Chun Liu1,*, Daode Zhang1, Wanfang Bai2

1 School of Computer Science, Hubei University of Technology, Wuhan, 430068, China
2 Xining Big Data Service Administration, Xining, 810000, China

* Corresponding Author: Chun Liu. Email: email

(This article belongs to the Special Issue: Optimization Algorithm in Real-World Applications)

Computers, Materials & Continua 2023, 76(2), 1479-1495. https://doi.org/10.32604/cmc.2023.038787

Abstract

The Honey Badger Algorithm (HBA) is a novel meta-heuristic algorithm proposed recently inspired by the foraging behavior of honey badgers. The dynamic search behavior of honey badgers with sniffing and wandering is divided into exploration and exploitation in HBA, which has been applied in photovoltaic systems and optimization problems effectively. However, HBA tends to suffer from the local optimum and low convergence. To alleviate these challenges, an improved HBA (IHBA) through fusing multi-strategies is presented in the paper. It introduces Tent chaotic mapping and composite mutation factors to HBA, meanwhile, the random control parameter is improved, moreover, a diversified updating strategy of position is put forward to enhance the advantage between exploration and exploitation. IHBA is compared with 7 meta-heuristic algorithms in 10 benchmark functions and 5 engineering problems. The Wilcoxon Rank-sum Test, Friedman Test and Mann-Whitney U Test are conducted after emulation. The results indicate the competitiveness and merits of the IHBA, which has better solution quality and convergence traits. The source code is currently available from: .

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Cite This Article

APA Style
Ye, Z., Zhao, T., Liu, C., Zhang, D., Bai, W. (2023). An improved honey badger algorithm through fusing multi-strategies. Computers, Materials & Continua, 76(2), 1479-1495. https://doi.org/10.32604/cmc.2023.038787
Vancouver Style
Ye Z, Zhao T, Liu C, Zhang D, Bai W. An improved honey badger algorithm through fusing multi-strategies. Comput Mater Contin. 2023;76(2):1479-1495 https://doi.org/10.32604/cmc.2023.038787
IEEE Style
Z. Ye, T. Zhao, C. Liu, D. Zhang, and W. Bai, “An Improved Honey Badger Algorithm through Fusing Multi-Strategies,” Comput. Mater. Contin., vol. 76, no. 2, pp. 1479-1495, 2023. https://doi.org/10.32604/cmc.2023.038787



cc Copyright © 2023 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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