摘要
文中针对蚁群算法收敛速度较慢、容易陷入局部最优解的缺点,在蚁群算法中引入遗传算法的精英策略,在挑选出精英蚂蚁后对其信息素的更新规则进行了改进,建立了新的蚁群算法模型。对于AGV在栅格图环境中最优路径的搜索问题,改进后的蚁群算法有着更高的搜索效率和更优的路径结果。
In this paper,aiming at the shortcomings of ant colony algorithm,such as slow convergence speed and easily falling into local optimal solutions,the elitist strategy of genetic algorithm was introduced into the ant colony algorithm. After the elite ants were selected,the update rules of their pheromone were improved,and a new ant colony algorithm model was established. For the optimal path search experiment of AGV in raster graph environment,the improved ant colony algorithm has higher search efficiency and better path results.
作者
孙宇翔
陈浩鹏
任传荣
SUN Yu-xiang;CHEN Hao-peng;REN Chuan-rong(Zhangjiagang Campus,Jiangsu University of Science and Technology,Zhangjiagang 215600,China)
出处
《物流工程与管理》
2022年第3期30-32,共3页
Logistics Engineering and Management
基金
基于混合蚁群算法的物流仓储AGV路径优化研究(126210019)。
关键词
AGV
路径优化
精英策略
蚁群算法
AGV
path optimization
elitist strategy
ant colony algorithm
作者简介
孙宇翔(2000-),男,汉族,江苏无锡人,本科,研究方向:物流管理;陈浩鹏(2000-),男,汉族,江苏盐城人,本科,研究方向:物流管理;通讯作者:任传荣(1980-),女,汉族,山东兰陵人,讲师,硕士研究生,研究方向:排序论。
