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引用本文：

王伯成,施锦丹,王凯.粒子群优化算法的研究现状与发展概述[J].电讯技术，2008，48（5）：7 - 11. [点击复制]
.Research Status and Review of the Development of Particle Swarm Optimization[J].，2008，48（5）：7 - 11. [点击复制]

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粒子群优化算法的研究现状与发展概述

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摘要:

粒子群优化算法(PSO)是基于群体智能的一种优化算法。该算法简单易于实现,可调参数少,得到了广泛的研究和飞速发展。介绍了PSO提出的背景、PSO的思想和原理,分析并总结了PSO的优缺点。根据PSO算法研究侧重点的不同,总结了PSO算法的发展现状及特点,分析并展望了PSO还需要完善或继续研究的问题,展望了PSO的研究热点及发展趋势。

关键词: 粒子群优化,复杂适应系统,群体智能

DOI：10.3969/j.issn.1001-893X.

修订日期：2008-02-04

基金项目:

Research Status and Review of the Development of Particle Swarm Optimization

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Abstract:

Particle Swarm Optimization(PSO) is an optimization technique based on swarm intelligenct.It is widely used and rapidly developed for its easy implementation and few particle required to be tuned.The background and the main idea of the principle of PSO are presented,the advantages and the shortcomings are summarized.According to the different directions of the research of PSO,the status quo of PSO is summarized,the characteristics is analyzed.The further research of PSO is presented and the trend of PSO development is prospected.

Key words: particle swarm optimization(PSO),complex adaptive system,swarm intelligence