粒子群优化算法

详细介绍了粒子群优化算法算法的由来、基本思想、特点及应用，对于初学者来说很容易入门一.导言二.基本PSO算法PSO算法优缺点吗PSO算法与其他智能算法的比较五PSO算法的改进六PS○算法收敛性分析七,PSO算法的应用体会导1.PSo算法的产生James Kennedy, Russell eberha在1995年发表了会议论文,标志着粒子群优化算法诞生Kennedy J, EberhartR C Particle swarmoptimization. IEEE International Conferenceon Neural NetworkS, Piscataway, NJ: IEEEPress,1995,1942-1948Russell c. eberhart receivedthe Ph. D. degree in electricalengineering from KansasState University, ManhattanHe is the chair and professorof Electrical and ComputerEngineering, Purdue Schoolof Engineering andRussell eberhart Technology, IndianaUniversity-Purdue Universityeberhart(engr.iupui. eduIndianapolis(IUPUI), Indianapolis, INJames KennedyKennedy Jim(abls. govJames Kennedy received the Ph. D. degree from theUniversity of North Carolina, Chapel Hill, in 1992. He iswith the U.S. Department of Labor, Washington, DCHe is a Social Psychologist who has been working withthe particle swarm algorithm since 1994James Kennedy, Russell C. Eberhart, Yuhui ShiSwarm Intelligence San Francisco: MorganKaufman Publishers, 2001sWA配 M INTELLIGENCHClerc M. Particle swarm optimizationLondon: ISTE Publishing Company, 2006曾建潮,介婧,崔志华.粒子群算法.北京:科学出版社,2004F. Van den Bergh. An Analysis of ParticleSwarm Optimizers. PhD Thesis. University ofPretoria. 2001张丽平.粒子群算法的理论与实践.杭州:浙江大学博士学位论文,2005导2.PSO算法基本思想粒子群算法模拟鸟集群飞行觅食的行为,鸟之间通过集体的协作使群体达到最优目的,是种基于 Swarm Intelligence的优化方法同遗传算法类似,也是一种基于群体迭代的子在解空间追随最优的粒子进行搜m但并没有遗传算法用的交双以及变异是粒PSO的优势在于简单容易实现同时又有深刻的智能背景,既活合科学研究,又特别适合工程应用,并且沒有许多参数需要调整。Swarm is better than personal