计算机工程与应用 ›› 2011, Vol. 47 ›› Issue (15): 245-248.

• 工程与应用 • 上一篇    

不确定环境下一种新的双蚁群路径规划算法

华 路,周之平   

  1. 南昌航空大学 信息工程学院,南昌 330063
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2011-05-21 发布日期:2011-05-21

Novel double ant colony path planning algorithm under uncertain environment

HUA Lu,ZHOU Zhiping   

  1. School of Information Engineering,Nanchang Hangkong University,Nanchang 330063,China

  • Received:1900-01-01 Revised:1900-01-01 Online:2011-05-21 Published:2011-05-21

摘要: 蚁群算法作为一种新型的模拟进化算法,被广泛地用于路径规划问题。但是传统的蚁群算法存在搜索时间长、收敛速度慢、易于陷入局部最优等缺点,为了克服算法的不足,该文提出一种改进的双蚁群算法,通过改变启发因子,同时引入最大最小蚁群系统思想对信息素进行更新以提高算法性能。实验结果表明,与同类算法相比,该算法能得到更优的路径。

关键词: 蚁群算法, 双蚁群算法, 启发因子, 路径规划, 最大最小蚂蚁系统

Abstract: Ant colony algorithm,as a novel simulation evolutionary algorithm,has been used in the path-planning problems widely.Because of some shortcomings such as long search the time low convergence and easy to trap into local optimization,in order to overcome these shortcomings,an improved double ant colony algorithm is presented in this paper,by changing heuristic factor and updating pheromone via incorporating maximum-minimum ant system.The experimental results indicate that the algorithm perform better than counterparts.

Key words: ant colony algorithm, double ant colony algorithm, heuristic factor, path planning, max-min ant system