摘要
对于传统的麻雀搜索算法(SSA)存在易陷入局部最优、后期寻优能力不足等问题,本文提出了一种改进的麻雀搜索算法(ISSA)。首先,在种群的初始化中引入Chebyshev混沌映射,提高种群的均匀性和多样性;其次,引入鲸鱼算法中的泡泡网法,对当前最优解进行扰动变异,使算法更容易规避局部最优问题;最后,引入黄金正弦算法更新跟随者位置,加快算法的收敛速度,增强全局搜索能力。通过对6个基准函数进行性能测试,将ISSA与4种基本算法进行对比,实验结果表明ISSA的性能有显著提高。
This paper proposed an improved sparrow search algorithm(ISSA)to solve the problems of the traditional sparrow search algorithm(SSA),such as easy to fall into local optimality and lack of late optimization ability.Firstly,Chebyshev chaotic mapping is introduced in the initialization of the population to increase the uniformity and diversity of the population;secondly,the bubble net method of whale algorithm is introduced to carry out perturbation and variation to the current optimal solution,so that the algorithm can jump out of the local optimal more easily;finally,the golden sine algorithm is introduced to update the follower position,accelerate the convergence rate of the algorithm,and enhance the global search ability.The performance of ISSA is tested by 6 benchmark functions,and then compared with 4 basic algorithms,the experimental results show that the performance of ISSA is significantly improved.
作者
杜乐
张毅
DU Le;ZHANG Yi(School of electrical and computer science,Jilin Jianzhu university,Changchun 130118,China)
出处
《吉林建筑大学学报》
CAS
2024年第5期77-82,共6页
Journal of Jilin Jianzhu University
基金
吉林省科技厅重点研发项目(20220203190SF).
