密集仓储环境下多AGV/RGV调度方法研究  

Research on Multi-AGV/RGV Scheduling Method in Intensive Storage Environment

作　　者：周亚勤[1] 汪俊亮 吕志军[1] 项前[1] 丁扬 张洁 ZHOU Yaqin;WANG Junliang;LÜZhijun;XIANG Qian;DING Yang;ZHANG Jie(School of Mechanical Engineering,Donghua University,Shanghai 201620)

机构地区：[1]东华大学机械工程学院,上海201620

出　　处：《机械工程学报》2021年第10期245-256,共12页Journal of Mechanical Engineering

基　　金：国家自然科学基金(51905091);上海市科技计划(20D?2251400);上海市工程技术研究中心能力提升计划(17DZ2283800)资助项目。

摘　　要：针对密集仓储环境下,出库作业时,有轨车(Rail guided vehicle,RGV)在不同货架间运送货物的换乘需要借助穿梭车(Automated guided vehicle,AGV)实现,入库作业时,货物先由穿梭车从输送带送达货架口,再由有轨车完成入库操作等特征,构建密集仓储环境下考虑多出入库任务的多AGV/RGV作业调度模型,包括穿梭车任务分配模型、协同有轨车选择模型和出入库完工时间数学模型。为实现密集仓储环境下的多AGV/RGV调度,提出适应不同出入库货位分布的穿梭车任务分配规则,实现考虑执行任务均衡的穿梭车任务分配;利用遗传算法实现多AGV/RGV出入库协同调度,对遗传算法关键解码算子进行详细设计,解码确定各穿梭车与有轨车执行出入库任务的顺序、任务的起始时间和结束时间,使得所有出入库任务的总完工时间最短。最后,通过某物流仓储企业实际案例进行测试,测试结果表明,提出的启发式规则能实现穿梭车任务的均衡分配,基于遗传算法的协同调度方法能有效地产生多AGV/RGV协同调度方案,减少出入库作业总时间,提高了仓储作业整体效率。For intensive warehouse storage operations,the automated guided vehicle(AGV)is needed to transfer the rail guided vehicle(RGV)between the shelves to transports the goods.When the storage is in operation,the AGV delivers the goods from the conveyor belt to the shelf,then RGV cooperates to complete the storage operations.It is important to construct a cooperative scheduling model for AGV/RGV considering the multiple warehousing tasks in an intensive storage environment,which includes AGV task assignment model,coordinated RGV selection model and completion time mathematical model.In order to realize multi-AGV/RGV scheduling problem,the task allocation rules of shuttle vehicles adapting to the distribution of different inbound and outbound cargo spaces are proposed with the objective of balancing the AGV tasks.Genetic algorithm(GA)is proposed to solve the multi-AGV/RGV inbound and outbound cooperation scheduling.The key decoding operator is designed in detail to determine the task sequence,task start and end time of AGV and RGV to perform the inbound and outbound tasks,so that the total completion time of all inbound and outbound operations is the shortest.Finally,the actual case of a logistics warehousing enterprise is tested.The case study demonstrates that the proposed heuristic rules can achieve the balanced distribution of AGV tasks,and the GA-based cooperative scheduling method can effectively generate multi-AGV/RGV coordinated scheduling scheme in terms of reducing the total time of warehousing operations and improving the overall efficiency of warehousing system.

关 键 词：AGV/RGV协同调度 密集仓储 遗传算法 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]