| 基于变惯性权重及动态邻域的改进PSO算法 |
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| 引用本文： | 姚灿中,杨建梅.基于变惯性权重及动态邻域的改进PSO算法[J].计算机工程,2011,37(21):20-22. |
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| 作者姓名： | 姚灿中 杨建梅 |
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| 作者单位： | 1. 华南理工大学经济与贸易学院,广州,510006
2. 华南理工大学工商管理学院,广州,510640 |
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| 基金项目： | 国家自然科学基金资助项目，教育部人文社会科学研究青年基金资助项目，中央高校基本科研业务费专项基金资助项目，广东省哲学社会科学"十一五"规划基金资助项目 |
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| 摘 要： | 分析并验证基于变惯性权重的粒子群优化(PSO)在粒子寻优过程中的有效性，论述类无标度网的特殊拓扑性质。将有向动态类无标度网作为粒子寻优邻域，提出一种基于变惯性权重及动态邻域的改进PSO算法。实验结果证明，与传统PSO算法相比，改进算法的寻优效果较好，可在一定程度上避免陷入局部最优。
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| 关 键 词： | 粒子群优化 类无标度网 惯性权重 度分布 邻域拓扑 |
| 收稿时间： | 2011-04-19 |
Improved PSO Algorithm Based on Variety Inertia Weight and Dynamic Neighborhood |
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| YAO Can-zhong,YANG Jian-mei.Improved PSO Algorithm Based on Variety Inertia Weight and Dynamic Neighborhood[J].Computer Engineering,2011,37(21):20-22. |
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| Authors: | YAO Can-zhong YANG Jian-mei |
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| Affiliation: | 1.School of Economics and Commerce,South China University of Technology,Guangzhou 510006,China;2.School of Business Administration,South China University of Technology,Guangzhou 510640,China) |
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| Abstract: | This paper analyzes and verifies the effectiveness of Particle Swarm Optimization（PSO） based on variety inertia weight in the particle optimization process,and discusses the special topological properties of scale-free like network.It uses the dynamic scale-free like network as the particle’s optimization neighborhood.It proposes an improved PSO algorithm based on variety inertia weight and dynamic neighborhood.Experimental results show that the improved algorithm performs better than the traditional PSO and may avoid falling into the local optimum instead. |
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| Keywords: | Particle Swarm Optimization（PSO） scale-free like network inertia weight degree distribution neighborhood topology |
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