J4 ›› 2012, Vol. 50 ›› Issue (02): 208-212.

• 数学 • 上一篇    下一篇

贪婪光线寻优算法的局部收敛性分析

沈继红1, 李加莲2   

  1. 1. 哈尔滨工程大学 理学院, 哈尔滨 150001|2. 哈尔滨工程大学 自动化学院, 哈尔滨 150001
  • 收稿日期:2011-04-25 出版日期:2012-03-26 发布日期:2012-03-21
  • 通讯作者: 李加莲 E-mail:lijialian@hrbeu.edu.cn

Local Convergence Analysis of Greedy Light RayOptimization Algorithm

SHEN Jihong1, LI Jialian2   

  1. 1. College of Science, Harbin Engineering University, Harbin 150001, China;2. College of Automation, Harbin Engineering University, Harbin 150001, China
  • Received:2011-04-25 Online:2012-03-26 Published:2012-03-21
  • Contact: LI Jialian E-mail:lijialian@hrbeu.edu.cn

摘要:

光线寻优算法局部搜索能力弱和收敛性理论完善困难的问题, 提出一种贪婪光线寻优算法, 并通过理论推导证明了该算法的局部收敛性. 数值实验结果表明, 对于单极值非线性标准测试函数, 与粒子群算法和模拟退火算法相比, 贪婪光线寻优算法具有更高的收敛精度和稳定性.

关键词: 费马原理, 智能优化, 光线寻优算法, 局部收敛性

Abstract:

Light ray optimization algorithm is a new intelligent optimization algorithm with the weak local optimization ability and the difficulty  of perfection of convergence theory. To solve these problems, greedy light ray optimization algorithm was proposed. Local convergence of the proposed  algorithm was proved via theoretical derivation. Numerical experimental  results show that for single extremal nonlinear standard testing functions, greedy light ray optimization algorithm has a higher convergent accuracy and stability  compared with particle swarm optimization and simulated  annealing.

Key words: Fermat’s principle, intelligent optimization, light ray optimization algorithm; local convergence

中图分类号: 

  • O224