Abstract: Based on a people-to-parts batch picking system of full container load, an order batching model takes picking equipment and commodity packaging volume into consideration is constructed, the objective of the model is to maximize the picking mileage. To solve the model, an order batching heuristic algorithm is proposed. With the data from a specific logistic center, a simulation experiment has been carried out. The results show that, the performance of D-eco（based on heuristic routing and mileage saving） is superior to FCFS（First Come First Service） and SBBM（Similarity Based Batching Method）, under 5 different order pool situations, the total picking distance optimized by D-eco is reduced by 12% and 2% compared with FCFS and SBBM.

Key words: batch picking, order batching, mileage saving, optimization of picking route, heuristic algorithm

摘要： 基于电商配送中心人到货整箱拣选系统，考虑拣选器具和商品包装体积，构造以最大化里程节约量为目标的订单分批模型，提出基于启发式拣选路径下节约里程的订单分批算法，并结合某企业物流中心订单数据对该算法进行仿真实验。研究结果表明，基于启发式路径下里程节约的订单分批方法（D-eco）的求解效果优于先到先服务分批方法（FCFS）和基于相似度的订单分批方法（SBBM）。在5种不同订单池容量下，采用D-eco进行订单分批后拣货人员总行走距离平均比FCFS和SBBM多缩减了12%和2%。

关键词: 批量拣选, 订单分批, 节约里程, 路径优化, 启发式算法