计算机与数字工程2025，Vol.53Issue(2)：338-346,9.DOI:10.3969/j.issn.1672-9722.2025.02.008
融合扰动策略的自适应哈里斯鹰优化算法
Adaptive Harris Hawks Optimization Algorithm Based on Disturbance Strategies
尚凯凯1
作者信息
- 1. 河北工程大学土木工程学院 邯郸 056038
- 折叠
摘要
Abstract
In order to improve the convergence accuracy of Harris hawks optimization algorithm and the ability of jumping out of the local optimization,an adaptive Harris hawks optimization algorithm based on disturbance strategies is proposed.Firstly,the diversity of the population is guaranteed by improving Tent chaotic map to produce more uniform population.Secondly,the nonlin-ear escape energy function strategy is introduced to balance the performance of local development and global search.Then,the opti-mal solution is mutated and disturbed by adaptive disturbance to avoid the premature phenomenon of the algorithm and improve the ability of the algorithm to jump out of local extremum.Finally,the ADHHO is used to simulate eight benchmark functions,and swarm intelligence optimization algorithms and improved HHO are compared for solution analysis.The results show that the pro-posed algorithm has certain advantages in convergence accuracy and anti-premature ability.关键词
哈里斯鹰优化算法/Tent混沌/非线性逃逸能量/自适应扰动Key words
Harris hawks optimization algorithm/Tent chaotic/nonlinear escape energy/adaptive disturbance分类
信息技术与安全科学引用本文复制引用
尚凯凯..融合扰动策略的自适应哈里斯鹰优化算法[J].计算机与数字工程,2025,53(2):338-346,9.
