通信学报2017，Vol.38Issue(8)：201-212,12.DOI:10.11959/j.issn.1000-436x.2017051
基于双变异策略的自适应骨架差分进化算法
Self-adaptive bare-bones differential evolution based on bi-mutation strategy
摘要
Abstract
Bare-bones differential evolution (BBDE) can elegantly solve the selection problem of control parameters and mutation strategy in differential evolution (DE).MGBDE is a classical BBDE based on bi-mutation strategy.However,it randomly assigns a mutation strategy to each individual,not considering their differences during evolution process,meanwhile it may suffer from premature convergence.To overcome these drawbacks,a modified algorithm based on MGBDE was proposed.A mutation strategy choice factor that guided the individual to choose a preferable mutation strategy at each mutation operation was introduced,avoiding the evolution blindness brought by the random selection of mutation strategy.To retain the almost parameter-free characteristic of bare-bones algorithm,the tuning of choice factor to be adapted was involved in the individual evolution,inspired by the concept of self-adaptive DE.The algorithm also included a well-designed stagnation perturbation mechanism to reduce the risk of trapping into the local optimal.Experimental results on 18 benchmark functions show that the proposed algorithm generally achieves better performance than state-of-the-art BBDE variants and several well-known DE algorithms in terms of convergence and robustness.关键词
差分进化/骨架算法/双变异策略/自适应Key words
differential evolution/bare-bones algorithm/bi-mutation strategy/self-adaptive分类
信息技术与安全科学引用本文复制引用
刘会宇,韩继红,袁霖,于波..基于双变异策略的自适应骨架差分进化算法[J].通信学报,2017,38(8):201-212,12.基金项目
国家自然科学基金资助项目(No.61309018)The National Natural Science Foundation of China (No.61309018) （No.61309018）
