Qianqian Zhang1, Yingmei Li1,*, Jianjun Zhan2,*, Shan Chen1
CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1251-1273, 2024, DOI:10.32604/cmc.2024.053892
- 15 October 2024
Abstract This research focuses on improving the Harris’ Hawks Optimization algorithm (HHO) by tackling several of its shortcomings, including insufficient population diversity, an imbalance in exploration vs. exploitation, and a lack of thorough exploitation depth. To tackle these shortcomings, it proposes enhancements from three distinct perspectives: an initialization technique for populations grounded in opposition-based learning, a strategy for updating escape energy factors to improve the equilibrium between exploitation and exploration, and a comprehensive exploitation approach that utilizes variable neighborhood search along with mutation operators. The effectiveness of the Improved Harris Hawks Optimization algorithm (IHHO) is assessed by… More >
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