一种基于Logistic混沌映射的骨干粒子群改进算法  

An Improved Algorithm for Backbone Particle Swarm Optimization Based on Logistic Chaotic Mapping

作　　者：朱雅敏[1] 薛鹏祥 

机构地区：[1]西安工业大学理学院,西安710021

出　　处：《西安文理学院学报（自然科学版）》2016年第1期1-4,11,共5页Journal of Xi’an University(Natural Science Edition)

基　　金：陕西省教育厅项目(14JK1347)

摘　　要：针对骨干粒子群算法因受初始化位置分布不均影响,易陷入局部最优的问题,提出一种基于Logistic混沌映射的改进算法,改进算法通过采用Logistic混沌映射控制来保证粒子初始化位置在搜索空间内保持随机分布,从而有效提升算法的搜索能力.仿真实验表明:与经典骨干粒子群算法相比,改进算法搜索能力有所增强,问题求解精度有明显提升.In this paper, aiming at the problem that the backbone particle swarm algorithm is easy to fall into local optimum because of uneven distribution of the initial position, an improved algorithm based on logistic chaotic mapping is proposed. By using the logistic chaotic mapping control to ensure that the initial position of particles in the search space to maintain a random distribution, therefore, the search ability of the algorithm is effectively improved. The simulation experiments show that the search ability of the improved algorithm has been significantly enhanced and its problem solving accuracy is significantly improved compared with that of the classical PSO algorithm.

关 键 词：骨干粒子群 LOGISTIC混沌映射 随机初始化 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]