计算机工程与应用 ›› 2009, Vol. 45 ›› Issue (14): 15-17.DOI: 10.3778/j.issn.1002-8331.2009.14.005

• 博士论坛 • 上一篇    下一篇

具有混沌局部搜索策略的差分进化全局优化算法

谭 跃1,2,谭冠政1   

  1. 1.中南大学 信息科学与工程学院,长沙 410083
    2.湖南城市学院 物电系,湖南 益阳 413000
  • 收稿日期:2009-01-20 修回日期:2009-02-23 出版日期:2009-05-11 发布日期:2009-05-11
  • 通讯作者: 谭 跃

Differential evolution algorithm with chaotic-local-search strategy for global optimization

TAN Yue1,2,TAN Guan-zheng1   

  1. 1.School of Information Science and Engineering,Central South University,Changsha 410083,China
    2.Department of Physics and Telecom Engineering,Hunan City University,Yiyang,Hunan 413000,China
  • Received:2009-01-20 Revised:2009-02-23 Online:2009-05-11 Published:2009-05-11
  • Contact: TAN Yue

摘要: 提出了一种具有混沌局部搜索策略的差分进化全局优化算法(CLSDE),它是在每一代中通过DE/best/1/bin形式的差分进化算法找到最佳个体,然后在最佳个体的附近用混沌的方法进行局部搜索。8个基本的测试函数优化结果表明:若误差函数精度为10-10,CLSDE寻优成功率比DE和SACDE都要高,而且收敛速度比DE和SACDE都要快。

Abstract: Differential Evolution Algorithm with chaotic-local-search strategy for global optimization(CLSDE) is proposed,which uses DE/best/1/bin to find the best individual each generation,and chaos-based local search is executed nearby the best individual.Experiment results on eight benchmark functions show that if the error function value is 10-10,both success rate of finding optimal solution and convergence speed using CLSDE are better than using DE and SACDE.