计算机工程与应用 ›› 2011, Vol. 47 ›› Issue (36): 54-56.

• 研究、探讨 • 上一篇    下一篇

基于邻域正交交叉算子的混合蛙跳算法

孟庆莹1,王联国2   

  1. 1.甘肃农业大学 工学院,兰州 730070
    2.甘肃农业大学 信息学院,兰州 730070
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2011-12-21 发布日期:2011-12-21

Shuffled frog leaping algorithm based on neighborhood orthogonal crossover operator

MENG Qingying1,WANG Lianguo2   

  1. 1.College of Engineering,Gansu Agricultural University,Lanzhou 730070,China
    2.College of Information Science Technology,Gansu Agricultural University,Lanzhou 730070,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2011-12-21 Published:2011-12-21

摘要: 混合蛙跳算法(SFLA)是一种全新的群体智能优化算法。针对基本混合蛙跳算法优化精度低、收敛速度慢的缺点,引入邻域正交交叉算子的概念,提出了一种基于邻域正交交叉算子的混合蛙跳算法(SFLA-OCO)。通过对基准函数进行测试,实验结果证明改进的算法提高了算法的收敛速度,增强了算法的寻优能力。

关键词: 混合蛙跳算法, 群体智能, 正交交叉算子

Abstract: Shuffled Frog Leaping Algorithm(SFLA) is a new swarm intelligence optimization algorithm.Since basic shuffled frog leaping algorithm has low optimization precision and slow convergence speed,this paper proposes a Shuffled Frog Leaping Algorithm based on neighborhood Orthogonal Crossover Operator(SFLA-OCO).Simulation?results?show that the new algorithm improves not only the convergence speed but?also?the?global?seach abilities.

Key words: shuffled frog leaping algorithm, swarm intelligence, orthogonal crossover operator