首页 | 本学科首页   官方微博 | 高级检索  
     

粒子群优化算法综述
引用本文:杨维,李歧强.粒子群优化算法综述[J].中国工程科学,2004,6(5):87-94.
作者姓名:杨维  李歧强
作者单位:山东大学控制科学与工程学院,济南,250061
基金项目:“八六三”高技术资助项目(2001AA413420),山东省自然科学基金资助项目(2003G01)
摘    要:粒子群优化(PSO)算法是一种新兴的优化技术,其思想来源于人工生命和演化计算理论。PSO通过粒子追随自己找到的最好解和整个群的最好解来完成优化。该算法简单易实现,可调参数少,已得到广泛研究和应用。详细介绍了PSO的基本原理、各种改进技术及其应用等,并对其未来的研究提出了一些建议。

关 键 词:群体智能  演化算法  粒子群优化
文章编号:1009-1742(2004)05-0087-08
收稿时间:8/5/2003 12:00:00 AM
修稿时间:9/8/2003 12:00:00 AM

Survey on Particle Swarm Optimization Algorithm
yangwei and lichiqiang.Survey on Particle Swarm Optimization Algorithm[J].Engineering Science,2004,6(5):87-94.
Authors:yangwei and lichiqiang
Abstract:Particle swarm optimization (PSO) is a new optimization technique originating from artificial life and evolutionary computation. The algorithm completes the optimization through following the personal best solution of each particle and the global best value of the whole swarm. PSO can be implemented with ease and few parameters need to be tuned. It has been successfully applied in many areas. In this paper, the basic principles of PSO are introduced at length, and various improvements and applications of PSO are also presented. Finally, some future research directions about PSO are proposed.
Keywords:swarm intelligence  evolutionary algorithm  particle swarm optimization
本文献已被 CNKI 维普 万方数据 等数据库收录!
点击此处可从《中国工程科学》浏览原始摘要信息
点击此处可从《中国工程科学》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号