摘要
为实现AGV完成作业任务行驶距离最短,建立了路径调节解决冲突的模型。分析蚁群算法的突出缺陷后,应用改进蚁群算法完成对多AGV系统的优化调度。最后以某车间内物料搬运多AGV调度优化为实例,利用matlab软件针对蚁群算法和改进蚁群算法进行实验对比,验证了改进蚁群算法在多AGV调度优化中的有效性。
In this paper, in order to shorten the traveling distance of the AGV as much as possible, we built a path scheduling and dispute solution model, then after analyzing the major shortcomings of the ant colony algorithm, used the improved ant colony algorithm to optimize the scheduling of the multiple AGV system, and at the end, in connection with the practical case of a certain workshop, proved the effectiveness of the improved ant colony algorithm in optimizing the muhi-AGV scheduling process.
出处
《物流技术》
2015年第23期87-89,115,共4页
Logistics Technology
基金
陕西省科学技术研究发展计划项目"缝纫机制造高速进给伺服驱动及动态性能"(2013k07-08)
关键词
自动导引小车
蚁群算法
作业调度
调度优化
AGV
ant colony algorithm
activity scheduling
scheduling optimization
