Adaptive Harris Hawks Optimization Algorithm Based on Disturbance Strategies
SHANG Kaikai
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.
Keywords：Harris hawks optimization algorithmTent chaoticnonlinear escape energyadaptive disturbance
Publication Date：2025-02-20
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：9( 338-346 )