Abstract: Aiming at the Harris Hawk Algorithm (HHO), which has unsatisfactory convergence speed, poor accuracy of optimization search, and easy to fall into local optimization, a combined multi-strategy improved Harris Hawk Algorithm (PTHHO) is proposed.Firstly, the initialization of Piecewise chaotic mapping is used to improve the quality and diversity of the population; secondly, an adaptive t-distribution strategy is introduced in the exploration phase to improve the convergence speed and accuracy; and finally, a dynamic reverse learning strategy is introduced in the development phase to enhance the algorithm's ability of jumping out of the local optimal solution.In the experiments, eight benchmark test functions are simulated to evaluate the algorithm's optimization seeking performance, and the GWO, HHO, CGWO, and PTHHO algorithms are compared and analyzed to verify the effectiveness of the improved strategy.
赵传哲, 王海波, 宋亚迪, 王荣林. 多策略融合的改进哈里斯鹰算法[J]. 吉林化工学院学报, 2024, 41(11): 60-66.
ZHAO chuanzhe, WANG haibo, SONG yadi, WANG ronglin. Improved Harris Hawk Algorithm for Multi-Strategy Fusion. Journal of Jilin Institute of Chemical Technology, 2024, 41(11): 60-66.
