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。
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.
出处
《计算机工程与应用》
CSCD
北大核心
2011年第15期245-248,共4页
Computer Engineering and Applications
基金
江西省教育厅项目(No.GJJ08221)
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
ant colony algorithm
double ant colony algorithm
heuristic factor
path planning
max-min ant system
