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Improved Harris Hawks optimization for global optimization and engineering design

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Abstract

Harris Hawks Optimization (HHO) is a novel meta-heuristic optimization algorithm. The algorithm is inspired by the behavior of Harris Hawks collaborating with each other to pursue prey in nature. The algorithm has the advantages of simple structure, fewer parameters, easy implementation, and excellent performance on high-dimensional problems. However, the algorithm also suffers from the inability to strike a good balance between exploration and exploitation, low convergence accuracy, and slow convergence speed in the early stage. In response to these defects, this paper will introduce three strategies to the HHO: a non-negative stochastic shrinkage exponential energy function, a Cauchy-Gaussian-based dynamic variance reduction selection strategy, and a greedy-difference-based selection strategy. The improved algorithm TSHHO is analyzed on the well-established 28 benchmark test functions, and four industrial engineering design problems. The experimental results show that the TSHHO algorithm proposed in this paper can achieve a better balance in the exploration and development stages,the strategies significantly improve the search efficiency, convergence accuracy, and robustness of the algorithm.

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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), Tianjin Research Innovation Project for Postgraduate Students (No. 2022SKYZ309).

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

    Lei Chen, Changzhou Feng & Yunpeng Ma

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  1. Lei Chen
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CL: methodology, writing—reviewing, supervision. FC: data collation and tabulation, writing—reviewing and editing and revise the manuscript; software. MY: Writing—reviewing and editing; plotting the figures.

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Correspondence to Lei Chen.

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Chen, L., Feng, C. & Ma, Y. Improved Harris Hawks optimization for global optimization and engineering design. Cluster Comput 27, 2003–2027 (2024). https://doi.org/10.1007/s10586-023-04020-y

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