Modified particle swarm optimization

Computer Engineering and Applications ›› 2008, Vol. 44 ›› Issue (9): 80-81.

• 理论研究 • Previous Articles Next Articles

Modified particle swarm optimization

WANG De-qiang,LUO Qi,QI Jia

School of Information and Control，Nanjing University of Information Science & Technology，Nanjing 210044，China

Received:2007-06-12 Revised:2007-08-13 Online:2008-03-21 Published:2008-03-21
Contact: WANG De-qiang

一种改进的粒子群优化算法

王德强,罗琦,祁佳

南京信息工程大学信息与控制学院，南京 210044

通讯作者: 王德强

Abstract

Abstract: Particle Swarm Optimization（PSO） algorithm is an evolutionary computation technique.It finds the optima of search spaces through the interaction of individuals in a population of particles.Based on the analysis of the evolutionary equations of the basic PSO algorithm，the paper proposes the modified PSO algorithm，which has better global optimal capability with faster evolution speed.The results of the five benchmark functions prove the model to be feasible.

Key words: particle swarm optimization, inertia weight, evolutionary computation

摘要： 粒子群优化算法（PSO）是一种生物进化技术。依据粒子间的相互影响发现搜索空间中的最优解。通过分析基本PSO算法的进化方程，研究了一种具有更好收敛速度和全局收敛性的改进PSO算法。5个典型测试函数的仿真实验表明该改进算法是行之有效的。

关键词: 粒子群优化, 惯性权重, 进化计算

WANG De-qiang,LUO Qi,QI Jia. Modified particle swarm optimization[J]. Computer Engineering and Applications, 2008, 44(9): 80-81.

王德强,罗琦,祁佳. 一种改进的粒子群优化算法[J]. 计算机工程与应用, 2008, 44(9): 80-81.

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Modified particle swarm optimization

一种改进的粒子群优化算法

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