江西科学2023，Vol.41Issue(6)：1039-1047,9.DOI:10.13990/j.issn1001-3679.2023.06.002
多策略融合的多目标萤火虫算法
Multi-objective Firefly Algorithm based on Multi-strategy Fusion
摘要
Abstract
In order to solve the problems such as weak exploration ability,poor convergence and poor distribution of multi-objective Firefly algorithm when dealing with complex optimization problems,this paper proposes a multi-objective Firefly algorithm based on multi-strategy fusion.Firstly,a combination of randomization and homogenization is used to initialize the population,ensuring the u-niformity and randomness of the initial population;Secondly,guided by the elite solution of ar-chives,the firefly movement is introduced into the firefly movement formula by introducing Levy flight random perturbation and adding mutation operators to avoid the population falling into local op-tima,balancing the algorithm's local search and de global exploration capabilities;Finally,a crow-ding distance mechanism is introduced to maintain external files to obtain evenly distributed Pareto frontiers.Comparing the MOFA-MSF algorithm with 5 classic algorithms and 7 recent algorithms,the results show that MOFA-MSF has good performance in exploration ability,convergence,and distribution.关键词
萤火虫算法/多目标优化/多策略/拥挤距离/莱维飞行/变异算子Key words
firefly algorithm/multi-objective optimization/multi-strategy/crowding distance/Lévy flight/mutation operator分类
信息技术与安全科学引用本文复制引用
黄建平,陈谣,邢文来,康平,赵嘉..多策略融合的多目标萤火虫算法[J].江西科学,2023,41(6):1039-1047,9.基金项目
江西省教育厅科技计划项目(GJJ2201506,GJJ2201803). （GJJ2201506,GJJ2201803）
