Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (3): 46-48.DOI: 10.3778/j.issn.1002-8331.2010.03.014

• 研究、探讨 • Previous Articles     Next Articles

Hybrid global optimization algorithm based on PSO and DE

WANG Jie-wen1,2,XIA Chang-qing1   

  1. 1.School of Materials Science and Engineering,Centre South University of China,Changsha 410083,China
    2.School of Information Technology,Hunan First Normal College,Changsha 410205,China
  • Received:2008-09-02 Revised:2008-10-23 Online:2010-01-21 Published:2010-01-21
  • Contact: WANG Jie-wen

一个基于PSO和DE的杂凑全局优化算法

王杰文1,2,夏长清1   

  1. 1.中南大学 材料科学与工程学院,长沙 410083
    2.湖南第一师范学院 信息技术系,长沙 410205
  • 通讯作者: 王杰文

Abstract: A hybrid global optimization algorithm,PSO-DE is presented,which is based on PSO and DE.In order to test PSO-DE,four benchmark functions are used,and the performance of the proposed PSO-DE algorithm is compared with PSO and DE,which demonstrate that it is a more effective global optimization algorithm with high solution quality in the space equal and less than 10 dimensions.

Key words: particle swarm optimization, differential evolution, hybrid algorithm, testing experiment

摘要: 结合粒子群优化算法和差分进化算法思想提出了一个杂凑的全局优化算法——PSO-DE,通过对4个基准测试函数的实验测试,并与PSO和DE算法比较,证明新算法在低维(≤10维)搜索空间可以获得更高质量的解。

关键词: 粒子群优化算法, 差分进化算法, 杂凑算法, 测试实验

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