摘要
对无人仓库中多AGV系统的避碰路径优化问题进行了研究,提出了一种基于弹性时间窗和改进蚁群算法的多AGV避碰路径优化策略.通过对传统蚁群算法改进启发式信息和信息素更新策略,来提高算法的执行速度和寻优能力,提出AGV任务优先级排序并改进冲突解决策略来解决多AGV之间的不同路径冲突.基于电商物流无人仓库的环境,利用MATLAB仿真软件对多AGV避碰路径规划进行建模分析.实验结果表明,基于弹性时间窗和改进蚁群算法的可以实现多AGV避碰路径规划,并能够短时间内找到避碰最优路径.
In this paper,the problem of collision avoidance path optimization for multi-AGV systems in unmanned warehouses is studied.A multi-AGV collision avoidance path optimization strategy based on elastic time window and improved ant colony algorithm is proposed.In this paper,the traditional ant colony algorithm is improved by heuristic information and pheromone update strategy to improve the execution speed and optimization ability of the algorithm.The priority scheduling of AGV tasks and the improvement of conflict resolution strategies are proposed to solve the different path conflicts bet ween multiple AGVs.Based on the environment of the e-commerce logistics unmanned warehouse,the MATLAB simulation software is used to model and analyze the multi-AGV collision avoidance path planning.The experimental results show that the multi-AGV collision avoidance path planning can be realized based on the elastic time window and the improved ant colony algorithm,and the optimal collision avoidance path can be found in a short time.
作者
杨洋
张建敏
刘艺林
宋馨
YANG Yang;ZHANG Jian-min;LIU Yi-lin;SONG Xin(School of Management of China University of mining and technology,Beijing 100083,China;ShiJiaZhuang Posts and Telecommunication Technical College,Shijiazhuang 050021,China)
出处
《数学的实践与认识》
北大核心
2020年第16期1-9,共9页
Mathematics in Practice and Theory
基金
中国矿业大学(北京)越崎青年学者资助
中国物流学会、中国物流与采购联合会研究课题面上项目资助(2019CSLKT3-117)
中央高校基础业务经费(2014QG01)
研究生科研创新能力提升项目(2020YJSGL06)。
关键词
多AGV系统
无人仓
蚁群算法
弹性时间窗
Multiple AGV system
unmanned warehouse
ant colony algorithm
elastic time window
