计算机工程与科学2024，Vol.46Issue(8)：1482-1492,11.DOI:10.3969/j.issn.1007-130X.2024.08.017
基于Fuch映射的改进白鲸优化算法及应用
Improved beluga whale optimization algorithms based on Fuch mapping and applications
摘要
Abstract
Aiming at the drawbacks of beluga whale optimization(BWO),such as low convergence accuracy,limited adaptive ability and weak anti-stagnation ability,two improved BWO algorithms based on Fuch mapping and dynamic opposition-based learning,namely,CIOEBWO and CPOEBWO,are pro-posed from the perspectives of chaos initialization,chaotic parameter,and nonlinear control strategy.Fuch chaotic initialization is used to increase the traversal of the initial population of BWO,which en-hances the optimization accuracy and convergence speed of the algorithm.In the phase of exploitation,Fuch chaotic mapping is introduced to dynamically adjust the parameter C1 to coordinate the capabilities of global search and local search,which improves the adaptive ability of BWO effectively.On the basis of two improvement strategies described above,the dynamic opposition-based learning strategy is intro-duced to enrich the number of high-quality individuals and enhance the overall anti-stagnation ability of the algorithm.The experimental results of 8 benchmark test functions and Friedman rank test indicate that the convergence accuracy,adaptive ability,and anti-stagnation ability of improved BWO are effec-tively improved.Compared with BWO and CIOEBWO,CPOEBWO has the better performance.In ad-dition,the optimization results of CPOEBWO and six comparison algorithms show that CPOEBWO has the stronger optimization ability and robustness.Finally,CPOEBWO is applied to solve the engineering optimization problems to demonstrate its applicability and effectiveness.关键词
白鲸优化算法/Fuch映射/动态反向学习/参数混沌策略/工程优化问题Key words
beluga whale optimization algorithm/Fuch mapping/dynamic opposition-based learning/chaotic parameter/engineering optimization problems分类
信息技术与安全科学引用本文复制引用
陈心怡,张孟健,王德光..基于Fuch映射的改进白鲸优化算法及应用[J].计算机工程与科学,2024,46(8):1482-1492,11.基金项目
贵州省省级科技计划(黔科合基础-ZK[2022]一般103) （黔科合基础-ZK[2022]一般103）
贵州省教育厅创新群体(黔科合支撑[2021]012) （黔科合支撑[2021]012）
贵州省教育厅青年科技人才成长项目(黔教合KY字[2022]138号) （黔教合KY字[2022]138号）
贵州大学科研基金资助项目(贵大特岗合字[2021]04号) （贵大特岗合字[2021]04号）
