递进式融合多策略的改进哈里斯鹰优化算法  

Improved Harris Hawk Optimization Algorithm with Progressive Integration Multi-strategy

作　　者：丁鑫 郭云川 张长胜[1] 钱斌[1] 张家洪 胡蓉[1] DING Xin;GUO Yunchuan;ZHANG Changsheng;QIAN Bin;ZHANG Jiahong;HU Rong(Faculty of Information Engineering and Automation,Kunming University of Science and Technology,Kunming 650500,China)

机构地区：[1]昆明理工大学信息工程与自动化学院,昆明650500

出　　处：《小型微型计算机系统》2024年第9期2126-2136,共11页Journal of Chinese Computer Systems

基　　金：国家自然科学基金项目(61963022,62173169)资助.

摘　　要：针对哈里斯鹰优化算法(HHO)易陷入局部最优、全局探索性能与局部开发能力不平衡等缺点,提出递进式融合多策略的改进哈里斯鹰优化算法(IHHO).首先,调整随机游走机制的位置更新方程以实现小范围优质勘探,提升该机制有效性,加强算法局部开发能力;其次,采用S型自适应能量控制因子,使算法能根据搜索进程合理调控捕猎行为,修正寻优模型;最后,融入定点重组与诱变策略,既保证种群优良基因集中于某一个体,又丰富种群多样性,算法局部寻优性能和局部极值规避能力并进增强.实验表明,所提改进方法以递进式提升算法性能,经耦合叠加效应后所得IHHO的搜索精度高、收敛速度快,并且具有较强实用性.An improved Harris hawk optimization algorithm with progressive integration multi-strategy(IHHO)is proposed,which compensates for the imperfections of the Harris hawk optimization algorithm(HHO),such as it is inclined to fall into local extremum and the global search performance not coordinated with the local exploitation capability.Firstly,revising the position update equation of the random walk mechanism realizes high-quality exploration in a small area,so as to promote its effectiveness and strengthen the local development ability of the algorithm;Secondly,the S-type adaptive energy control factor is used to make the algorithm reasonably regulate the hunting behavior according to the search process and modify the optimization model.Finally,integrating the site-directed recombination and mutagenesis strategy into the algorithm,not only ensured that the valuable genes were concentrated in a certain individual but also enriched the diversity of the population,the local optimization performance and the local extreme value avoidance ability of the algorithm enhanced simultaneously.The performance of the algorithm is progressively improved by the proposed improved method,and the IHHO obtained by coupling superposition effect has high search accuracy,fast convergence speed,and superior practicability,which are reflected in the experimental results.

关 键 词：哈里斯鹰优化算法(HHO) 融合多策略 位置更新方程 能量控制因子 定点重组与诱变策略 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]