基于混沌粒子群优化算法研究与进展  

Research and Progress Based on Chaotic Particle Swarm Optimization Algorithm

作　　者：赵宇红[1] 邵玉林[1] 廉莉莉[1] 

机构地区：[1]南华大学电气工程学院,湖南衡阳421001

出　　处：《工业控制计算机》2012年第11期52-53,共2页Industrial Control Computer

摘　　要：粒子群算法简单,只需要初等的数学知识就可以理解,但粒子群算法的工作机理到现在还是没有得到彻底而详细的分析研究,它属于一种还在发展的算法,PSO在优化复杂的多峰函数时,常常会陷入到局部极值点等缺点。混沌是存在非线性系统中的一种较为普遍的现象,具有随机性、遍历性和内在规律性的特点,尤其是混沌遍历性的特点,将混沌局部搜索引入到粒子群算法中,提出了混沌粒子群算法,改进了粒子群算法易陷入局部极值的不足,提高了算法的收敛速度,论述了混沌粒子群优化算法的研究与进展。It is simple for Particle swarm algorithm which needs elementary mathematical knowledge to understand,but the working mechanism in the particle swarm algorithm is still not got completed and detailed analysis research.Which belongs to a kind of growing algorithm,PSO in optimization of complex multimodal function,will often fall into the local extreme points and other shortcomings.Chaos is the presence of nonlinear system of a relatively common phenomenon,randomicity,ergodicity and intrinsic regularity characteristics,especially the chaos ergodicity,the chaotic local search into the particle swarm algo- rithm,chaotic particle swarm algorithm,improved particle swarm algorithm easily into the local extremum deficiency,improve the Speed of convergence Discussed the chaos particle swarm optimization algorithm research and progress.

关 键 词：混合优化算法 粒子群算法 混沌优化算法 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]