| 一种惯性权重动态调整的新型粒子群算法 |
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| 引用本文： | 刘建华,樊晓平,瞿志华.一种惯性权重动态调整的新型粒子群算法[J].计算机工程与应用,2007,43(7):68-70. |
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| 作者姓名： | 刘建华 樊晓平 瞿志华 |
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| 作者单位： | [1]中南大学信息科学与工程学院,长沙410083 [2]美国中佛罗里达大学电气与计算机工程系,奥兰多,FL32816—2450 [3]福建师范大学数学与计算机科学学院,福州350007 |
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| 摘 要： | 在简要介绍基本PSO算法的基础上，提出了一种根据不同粒子距离全局最优点的距离对基本PSO算法的惯性权重进行动态调整的新型粒子群算法（DPSO）．并对新算法进行了描述。以典型优化问题的实例仿真验证了DPSO算法的有效性。
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| 关 键 词： | 粒子群算法(PSO算法) 全局最优性 动态粒子群算法(DPSO) 收敛性 |
| 文章编号： | 1002-8331（2007）07-0068-03 |
| 修稿时间： | 2006-07 |
New Particle Swarm Optimization algorithm with dynamic change of inertia weights |
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| LIU Jian-hua,FAN Xiao-ping,QU Zhi-hua.New Particle Swarm Optimization algorithm with dynamic change of inertia weights[J].Computer Engineering and Applications,2007,43(7):68-70. |
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| Authors: | LIU Jian-hua FAN Xiao-ping QU Zhi-hua |
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| Affiliation: | LIU Jian-hua,FAN Xiao-ping,QU Zhi-hua(1.College of Information Science and Engineering,Central South University,Changsha 410083 ,China; 2.Department of Electrics ＆ Computer Engineering,University of Central Florida,Orlando,FL 32816-2450,USA ;3.College of Mathematics and Computer Science,Fujian Normal University,Fuzhou 350007,China) |
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| Abstract: | Particle Swarm Optimization(PSO) is a new population-based intelligence algorithm and exhibits good performance on optimization.In fact,PSO is a random evolution algorithm.However,during the evolution of the algorithm,the magnitude of inertia weight has impact on the exploration and convergence of PSO,which is a contradiction.In this paper,a new PSO algorithm,called as DPSO,is proposed in which the inertia weight of every particle will be changed dynamically with the distance between the particle and the current optimal position.Experiments on benchmark functions show that DPSO outperforms standard PSO. |
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| Keywords: | Particle Swarm Optimization(PSO) global optimality DPSO convergence |
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