Solving the joint order batching and picker routing problem, as a clustered vehicle routing problem

?The Joint Order Batching and Picker Routing Problem (JOBPRP) is a very promising approach to minimize the order picking travel distance in a picker-to-parts warehouse environment. We show that this JOBPRP can be modelled as a clustered vehicle routing problem (CluVRP) by replacing vehicles by batches, clusters by orders and customers by pick locations. To solve this cluster-based model of the JOBPRP,we implement a two-level Variable Neighborhood Search (2level-VNS) meta-heuristic as used earlier for the CluVRP, and study which adaptations are required to perform e ciently in a warehouse environment. Additionally, we test if the Hausdor? distance used for the CluVRP can serve as a valid clustering criterion for order batching. We implement the Hausdor? distance in two di?erent ways in our batching heuristic, and compare the performance with the cumulative minimal aisles visited-criterion, known as a well-performing batching metric in rectangular warehouses with parallel aisles. Finally, we show that the CluVRP model solved by the 2level-VNS approach performs well compared to state-of-the-art algorithms for the OBP in single-block warehouses. Only a multi-start VNS approach published recently obtains slightly be?er solutions. Concerning the Hausdor? distance, we must conclude that in most experiments the minimum-aisles criterion retains a be?er ?t in this warehouse context.