摘要
粒子群优化算法是一种新兴的基于群智能的演化计算方法,其思想来源于对鸟群运动行为的研究。群体中的每一个粒子通过追随个体最优解和群体最优解来完成解的迭代过程。首先介绍了PSO算法的基本原理,然后对PSO的几种典型改进算法进行了介绍并通过仿真实验对各种算法进行了分析和比对,最后对粒子群算法研究方向进行了展望。
Particle swarm optimization algorithm is a kind of new evolutionary computation technology. The algorithm completes the iterative process through following the personal best solution and the global best value. The basic principles of PSO are introduced firstly. Then several typical improved algorithms of PSO axe introduced and analyzed and compared by simulation experiment. Finally, future research issues are given.
出处
《计算机与现代化》
2009年第7期22-25,共4页
Computer and Modernization
关键词
粒子群优化
群智能
演化
particle swarm optimization
swarm intelligence
evolutionary computation
