智能RGV的动态调度策略研究  

Research on Dynamic Scheduling Strategy of Intelligent RGV

作　　者：陈颖 葛显龙 Chen Ying;Ge Xianlong(School of Economics & Management,Chongqing Jiaotong University,Chongqing 400074,China)

机构地区：[1]重庆交通大学经济与管理学院,重庆400074

出　　处：《物流技术》2019年第4期35-43,共9页Logistics Technology

基　　金：国家自然科学基金项目资助(71502021);教育部人文社会科学基金项目资助(14YJC630038;15XJC630007);博士后科学基金特别资助(2016T90862);重庆市基础与前沿研究项目资助(cstc2016jcyjA0160);重庆市科学技术研究项目(KJ1500702)

摘　　要：针对自动化立体仓库中智能Rail Guided Vehicle小车(以下简称RGV)的动态调度问题,对于单工序加工动态调度建立了单目标优化、最短路模型,求得最小支撑树,即耗时最短的工艺路线,由此得到单工序加工的最优调度。针对多工序加工动态调度问题,考虑存在设备柔性和工艺路线的柔性,首先要解决设备的分配问题,其次是调度过程中RGV对信号的响应原则,建立多目标优化模型,利用0-1整数规划求解使得物料加工完所有工序的时间最短,由此得到多工序加工的优化调度。最后得出了不同工序的加工时长对RGV的动态调度和生产车间的最大产量起到了绝对性的影响,RGV的作业参数变化对模型影响极小。Aiming at the dynamic scheduling problem of the intelligent Rail Guided Vehicle(RGV)in an automated stereoscopic warehouse,a single-objective optimization and shortest path model is established for the dynamic scheduling of a single-job process to obtain the minimal spanning tree,i.e.the shortest time-consuming route of the process,thus arriving at its optimal scheduling.Then aiming at the dynamic scheduling problem of the multi-job process,and considering the flexibility of the equipment and the process route,the equipment allocation problem is firstly solved.Next the signal response principle of the RGV in the scheduling process is established,for which,a multi-objective optimization model is set up,and the 0-1 integer programming used to minimize the time needed for finishing all the jobs of the process,thus optimizing its scheduling.At the end,it is concluded that the processing time of the different jobs has absolute influence on the dynamic scheduling of the RGV and the maximum output of the workshop,and the change of the RGV operation parameters has little influence on the model.

关 键 词：RGV 多目标优化 最短路问题 动态调度 最小支撑树 0-1整数规划 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置] TP23[自动化与计算机技术—控制科学与工程]