To improve the operational efficiency of e-commerce warehouses, multi-location storage systems which means each stock keeping unit can be stored in multiple locations or a location can contain multiple stock keeping units, have been developed and applied in practice. When orders are picked in a batch, how to select the picking location from storage locations holding the identical stock keeping unit obviously affects how far the pickers must travel to complete the picking tasks. However, few works have systematically studied how to optimize order batch picking from the perspective of different storage systems. This paper formulated the order batch picking optimization problems for three typical storage systems and developed the algorithm package including location interval distance algorithm, location selection algorithm, routing algorithm and order batching algorithm to tackle them. Our work is particularly capable to covering the situation of multi-location storage system. The numerical experiment results show that the performance of the proposed algorithm combinations is satisfactory to solve the problems with different size both in solution quality and computation efficiency. The applicable algorithm combinations used in practice are also recommended by comparative analysis. Our study can provide valuable decision reference to warehouse managers for operating batch picking system especially under multi-location scenarios efficiently.

为了提高电子商务仓库的运营效率，已经开发并应用了多位置存储系统，这意味着每个库存单位可以存储在多个位置或一个位置可以包含多个库存单位。批量拣选订单时，如何从拥有相同库存单位的存储地点中选择拣选地点显然会影响拣选人员必须走多远才能完成拣选任务。但是，从不同的存储系统的角度来看，很少有系统地研究如何优化订单批拣选。提出了三种典型存储系统的订单批量拣选优化问题，并开发了包括位置间隔距离算法，位置选择算法，路由算法和订单批处理算法来解决它们。我们的工作特别有能力涵盖多位置存储系统的情况。数值实验结果表明，所提出的算法组合能够很好地解决求解质量和计算效率方面大小不同的问题。比较分析还建议在实践中使用适用的算法组合。我们的研究可以为仓库经理有效地操作批次分拣系统提供有价值的决策参考，尤其是在多地点情况下。数值实验结果表明，所提出的算法组合能够很好地解决求解质量和计算效率方面大小不同的问题。比较分析还建议在实践中使用适用的算法组合。我们的研究可以为仓库经理有效地操作批次分拣系统提供有价值的决策参考，尤其是在多地点情况下。数值实验结果表明，所提出的算法组合能够很好地解决求解质量和计算效率方面大小不同的问题。比较分析还建议在实践中使用适用的算法组合。我们的研究可以为仓库经理有效地操作批次分拣系统提供有价值的决策参考，尤其是在多地点情况下。