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 nichemechanism and its application

作　　者：李大海 李鑫 王振东 Li Dahai;Li Xin;Wang Zhendong(School of Information Engineering,Jiangxi University of Science&Technology,Ganzhou Jiangxi 341400,China)

机构地区：[1]江西理工大学信息工程学院,江西赣州341400

出　　处：《计算机应用研究》2024年第4期1077-1085,共9页Application Research of Computers

基　　金：国家自然科学基金资助项目(61563019,615620237);江西理工大学校级基金资助项目(205200100013)。

摘　　要：针对麻雀搜索算法SSA易陷入局部最优、算法过早收敛等问题,提出一种融合小生境的麻雀搜索算法NSSA。首先,NSSA使用一种基于发现者相似性形成自适应物种的小生境策略将麻雀种群自动划分为以发现者为中心的若干个小种群或物种,且使跟随者朝所属物种内的发现者位置移动,以保持种群的多样性。其次,通过结合模糊逻辑的差分变异并使用发现者所属物种内的其他个体信息对发现者进行变异操作,以提高算法跳出局部最优的能力。选用CEC2017测试集中的12个函数作为实验测试集,将NSSA与CSSOA、ISSA、MSSSA、SHSSA、MSWOA进行性能测试。实验结果表明,在大多数多峰目标函数上,NSSA与排名第二的算法相比,收敛精度提升了10%以上。对NSSA的各改进策略进行了消融实验,结果表明,在综合改进策略的共同作用下,NSSA的综合优化性能排名第一。最后将NSSA应用于压力容器设计问题,结果表明,相比于其他算法,NSSA仍能够获得最优的解。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 sparrow 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%compared with the second ranked evaluated algorithm on most of multimodal objective test functions.This paper also conducted ablation experiments for each improved strategy proposed in NSSA.Experimental results show NSSA can achieve supreme performance by applying all 3 strategies simultaneously.At last,NSSA is applied to solve the pressure vessel design problem.Experimental 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 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]