The order batching problem is a combinatorial optimization problem that arises in the warehouse order picking process. In the order batching problem, the aim is to find groups of orders and picking routes of these groups to minimize distance travelled by the order picker. This problem is encountered especially in manual order picking systems where the capacity of picking vehicle is limited. Solving the order batching problem becomes more important when the size of the problem (e.g. number of storage locations, number of aisles, number of customer orders, etc.) is large. The content of the batch and picking route affect the retrieval-time of the orders. Therefore, an effective batching and routing approach is essential in reducing the time needed to collect ordered items. The main objective of this study is to develop fast and effective metaheuristic approaches to solve the order batching problem. For this purpose, two genetic algorithm based metaheuristic approaches are proposed. The numerical test of the proposed algorithms is performed with generated data sets. The proposed methods are thought to be useful to solve real-life problems in different warehouse configurations. Accordingly, a real case study is conducted in the distribution center of a well-known retailer in Turkey. The case study includes the storage assignment process of incoming products. The results demonstrate that developed algorithms are practical and useful in real-life problems.

订单批处理问题是在仓库订单拣配过程中出现的组合优化问题。在订单批处理问题中，目标是找到订单组和这些组的拣选路线，以最大程度地减少拣选人员的行进距离。特别是在拣选车的能力受到限制的手动拣选系统中会遇到这个问题。当问题的规模（例如，存储地点数量，过道数量，客户订单数量等）很大时，解决订单批处理问题就变得尤为重要。批次的内容和拣配路线会影响订单的检索时间。因此，有效的批处理和路由方法对于减少收集订购物品所需的时间至关重要。这项研究的主要目的是开发快速有效的元启发式方法来解决订单批处理问题。为此，提出了两种基于遗传算法的元启发式方法。所提出算法的数值测试是通过生成的数据集进行的。所提出的方法被认为对于解决不同仓库配置中的实际问题很有用。因此，在土耳其一家知名零售商的分销中心进行了实际案例研究。案例研究包括进货产品的存储分配过程。结果表明，开发的算法在实际问题中是实用且有用的。所提出算法的数值测试是通过生成的数据集进行的。所提出的方法被认为对于解决不同仓库配置中的实际问题很有用。因此，在土耳其一家知名零售商的分销中心进行了实际案例研究。案例研究包括进货产品的存储分配过程。结果表明，开发的算法在实际问题中是实用且有用的。所提出算法的数值测试是通过生成的数据集进行的。所提出的方法被认为对于解决不同仓库配置中的实际问题很有用。因此，在土耳其一家知名零售商的分销中心进行了实际案例研究。案例研究包括进货产品的存储分配过程。结果表明，开发的算法在实际问题中是实用且有用的。