计算机应用研究2024，Vol.41Issue(4)：1077-1085,9.DOI:10.19734/j.issn.1001-3695.2023.08.0353
融合小生境机制的增强麻雀搜索算法及其应用
Enhanced sparrow search algorithm by integrating niche mechanism and its application
摘要
Abstract
Aiming at overcoming drawbacks of lower accuracy and being trapped easily into local optimums of the sparrow search algorithm(SSA),this paper proposed an enhanced sparrow search algorithm by integrating niche mechanism(NSSA).Firstly,NSSA adopted an adaptive niche mechanism based on producers'similarity to automatically partition the whole spar-row population into several producer-centered speciation,and to move scroungers inside the speciation towards to the producer inside the same speciation,in order to maintaining the diversity of the whole population.Secondly,NSSA applied a fuzzy logic based differential mutation operation to further mutate sparrow producers to raise the probability to jump out of local optimums.It used 12 functions selected from the CEC2017 benchmark function as the testbed to evaluate NSSA with CSSOA,ISSA,MSSSA,SHSSA,and MSWOA.Experimental results show that NSSA even can raise convergence accuracy up by 10％com-pared with the second ranked evaluated algorithm on most of multimodal objective test functions.This paper also conducted ab-lation experiments for each improved strategy proposed in NSSA.Experimental results show NSSA can achieve supreme per-formance by applying all 3 strategies simultaneously.At last,NSSA is applied to solve the pressure vessel design problem.Ex-perimental results illustrate that NSSA has the ability to find the best solutions compared to other evaluated algorithms.关键词
麻雀搜索算法/小生境/差分变异操作/模糊逻辑/压力容器设计Key words
sparrow search algorithm(SSA)/niche/difference mutation operation/fuzzy logic/pressure vessel design分类
信息技术与安全科学引用本文复制引用
李大海,李鑫,王振东..融合小生境机制的增强麻雀搜索算法及其应用[J].计算机应用研究,2024,41(4):1077-1085,9.基金项目
国家自然科学基金资助项目(61563019,615620237) （61563019,615620237）
江西理工大学校级基金资助项目(205200100013) （205200100013）
