基于混沌搜索的粒子群优化算法  

Particle Swarm Optimization Algorithm Based on Chaos Searching

作　　者：杨俊杰[1] 周建中[1] 喻菁[1] 吴玮[1] 

机构地区：[1]华中科技大学水电与数字化工程学院,武汉430074

出　　处：《计算机工程与应用》2005年第16期69-71,共3页Computer Engineering and Applications

摘　　要：粒子群优化算法(PSO)是一种有效的随机全局优化技术。文章把混沌优化搜索技术引入到PSO算法中,提出了基于混沌搜索的粒子群优化算法。该算法保持了PSO算法结构简单的特点,改善了PSO算法的全局寻优能力,提高的算法的收敛速度和计算精度。仿真计算表明,该算法的性能优于基本PSO算法。Particle swarm optimization(PSO) algorithm is one of the most powerful methods for solving unconstrained and constrained global optimization problems.This paper incorporates chaos optimization algorithm into the PSO algorithm,and propose a new particle swarm optimization algorithm based on chaos searching(CPSO).The proposed algorithm has not only the simple for implement of original particle swarm optimization,also the fast convergence and high computational precision of chaos optimization algorithm.The computational results on several benchmark problems have shown the proposed algorithm is superior to original particle swarm optimization.

关 键 词：粒子群优化算法 混沌 优化 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]