结合``货到人''仓储系统的订单拣选场景, 在考虑订单中各种商品订购数量和货 箱中商品存储量的情况下, 研究了自动小车存储及取货系统的订单分批拣选问题. 对于给定 的待拣选订单, 以货箱出库次数极小化为目标, 建立了订单分批问题的整数规划模型, 并利用聚 类思想设计了两阶段启发式算法. 利用不同规模的算例进行仿真实验, 验证了模型和算法的有效 性. 通过对比按照本文模型和算法得到的分批结果与按照先到先服务策略得到的分批结果, 可以 发现, 按照文章模型和算法进行订单分批, 拣选效率大约提升了25\%--45\%. 进一步分析了拣选 台容量和相似度加权系数等参数变化对订单分批结果的影响. 最后利用两个具体算例, 对比分析了考虑商品订购数量和不考虑商品订购数量的订单分批模型之间的关系, 验证了考虑商品订购数量的订单分批模型的优越性.

Based on the scene of ``parts-to-picker'' warehouse system, the order batching problem of autonomous vehicle storage and retrieval system is studied by considering the quantity of every item in orders and SKU bins. Given a set of orders to be picked, the order batching problem is formulated into an integer programming model, the goal of the model is to minimize the number of SKU bins to be transported. A two-stage heuristic algorithm is designed based on the clustering idea. Simulation experiments are carried out on different size of examples to verify the effectiveness of the model and algorithm. By comparing with the order batching results obtained by the first-come-first-served strategy, we find that the picking efficiency can be improved by 25\%--45\% based on the batching results obtained by the model and algorithm of this paper. Furthermore, the sensitivity analysis is done on parameters of the picking station's capacity and the weighted coefficient of similarity. Finally, the relationship between the order batching model considering the quantity of items in orders and the order batching model without considering the quantity of items in orders is compared and analyzed by using two examples. And the superiority of the order batching model considering the quantity of items in orders is verified