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Harris hawks optimization based on global cross-variation and tent mapping

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Abstract

Harris hawks optimization (HHO) is a new meta-heuristic algorithm that builds a model by imitating the predation process of Harris hawks. In order to solve the problems of poor convergence speed caused by uniform choice position update formula in the exploration stage of basic HHO and falling into local optimization caused by insufficient population richness in the later stage of the algorithm, a Harris hawks optimization based on global cross-variation and tent mapping (CRTHHO) is proposed in this paper. Firstly, the tent mapping is introduced in the exploration stage to optimize random parameter q to speed up the convergence in the early stage. Secondly, the crossover mutation operator is introduced to cross and mutate the global optimal position in each iteration process. The greedy strategy is used to select, which prevents the algorithm from falling into local optimal because of skipping the optimal solution and improves the convergence accuracy of the algorithm. In order to investigate the performance of CRTHHO, experiments are carried out on ten benchmark functions and the CEC2017 test set. Experimental results show that the CRTHHO algorithm performs better than the HHO algorithm and is competitive with five advanced meta-heuristic algorithms.

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Acknowledgements

The authors would like to thank the anonymous reviewers for their valuable comments and suggestions.

Funding

This study was supported by the National Natural Science Foundation of China (No. 61535008), the Natural Science Foundation of Tianjin (No. 20JCQNJC00430), the National Natural Science Foundation of China (No. 62203332) and the Science and Technology Research Team in Higher Education Institutions of Hebei Province (No. ZD2018045).

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Authors and Affiliations

  1. School of Information Engineering, Tianjin University of Commerce, Beichen District, Tianjin, 300134, China

    Lei Chen & Yunpeng Ma

  2. School of Science, Tianjin University of Commerce, Beichen District, Tianjin, 300134, China

    Na Song

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  1. Lei Chen
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Contributions

CL was responsible for methodology, writing and reviewing, and supervision. SN was involved in data collation and tabulation, writing, reviewing, and editing, revising the manuscript and software. MY took part in writing, reviewing, and editing; and plotting the figures.

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Correspondence to Lei Chen.

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Chen, L., Song, N. & Ma, Y. Harris hawks optimization based on global cross-variation and tent mapping. J Supercomput 79, 5576–5614 (2023). https://doi.org/10.1007/s11227-022-04869-7

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