【摘要】 为解决烟叶原料出入库作业中存在的人工依赖度高、作业效率低、流程不规范等问题，基于仓库原有布局提出了一种烟叶原料出入库自动化方案，将烟叶原料仓库出入库作业流程规范化；构建了叉车AGV-运输AGV协同作业优化模型，并设计了两阶段协同优化算法，即在叉车AGV任务组预分配阶段采用模拟退火算法，在运输AGV协同调度阶段采用带精英策略的快速非支配排序遗传算法（NSGA-II）。以浙江中烟工业有限责任公司烟叶原料仓库为对象进行仿真测试，结果表明：采用模拟退火算法进行叉车AGV任务组预分配可使叉车AGV的完工时间差值比传统人工分配策略缩短500 s以上，并优化任务最大完工时间10%以上；采用NSGA-II进行运输AGV协同调度后的任务最大完工时间比随机协同分配减少25%以上。该方法可为提高烟叶原料仓库系统出入库作业效率提供支持。更多还原

【Abstract】 To reduce the reliance on manual labor in tobacco raw material receiving/retrieving,improve operational efficiency, and standardize operational procedures, an automation scheme for tobacco receiving/retrieving was proposed based on the original layout of the warehouse. An optimization model for the collaborative operation of forklift AGVs and transport AGVs was configured,and a two-stage collaborative optimization algorithm was designed,namely a simulated annealing algorithm for the job pre-assignment stage of the forklift AGVs, and a fast non-dominated sorting genetic algorithm Ⅱ（NSGA-Ⅱ）for the co-scheduling stage of the transport AGVs. A simulation test was conducted using the tobacco warehouse of China Tobacco Zhejiang Industrial Limited Corporation as the object,and the results showed that the adoption of the simulated annealing algorithm to the job pre-assignment reduced the differences of completion time by more than 500 seconds and the maximum task completion time by more than 10% compared with the traditional manual assignment strategy,and the adoption of NSGA-Ⅱto the co-scheduling of transport AGVs reduced the maximum task completion time by more than 25%compared with the random co-assignment algorithm. This method helps to promote the efficiency of tobacco receiving/retrieving in the tobacco warehouse.更多还原