Improved HHO algorithm based on good point set and nonlinear convergence formula  

作　　者：Guo Hairu Meng Xueyao Liu Yongli Liu Shen 

机构地区：[1]School of Computer Science and Technology,Henan Polytechnic University,Jiaozuo 454000,China

出　　处：《The Journal of China Universities of Posts and Telecommunications》2021年第2期48-67,共20页中国邮电高校学报（英文版）

基　　金：supported by the National Natural Science Foundation of China(61872126)。

摘　　要：Harris hawks optimization(HHO)algorithm is an efficient method of solving function optimization problems.However,it is still confronted with some limitations in terms of low precision,low convergence speed and stagnation to local optimum.To this end,an improved HHO(IHHO)algorithm based on good point set and nonlinear convergence formula is proposed.First,a good point set is used to initialize the positions of the population uniformly and randomly in the whole search area.Second,a nonlinear exponential convergence formula is designed to balance exploration stage and exploitation stage of IHHO algorithm,aiming to find all the areas containing the solutions more comprehensively and accurately.The proposed IHHO algorithm tests 17 functions and uses Wilcoxon test to verify the effectiveness.The results indicate that IHHO algorithm not only has faster convergence speed than other comparative algorithms,but also improves the accuracy of solution effectively and enhances its robustness under low dimensional and high dimensional conditions.

关 键 词：HHO algorithm local optimum good point set nonlinear formula MULTI-DIMENSION 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]