Abstract

AbstractWarehouses have gained considerable attention in recent years, especially due to the increasing interest for e-commerce. Order picking is the process of finding and removing products from a warehouse to fulfil customer orders. Order picking is the most time-consuming and costly operation in manual picker-to-parts warehouses. Order picking problem is similar to Traveling Salesman Problem in the sense that the order picker corresponds to the salesman whereas items to be picked correspond to cities to be visited. Hence, order picking problem is known to be NP-hard. The objective of order picking problem is to minimize total travelled distance of an order picker. For only single-block and two-block traditional rectangular warehouses, optimal picker routing can be found. However, there is no optimal algorithm for three or more block traditional rectangular warehouses. Some popular routing heuristics are applied for single-block and multi-block traditional rectangular warehouses, such as S-Shape, Largest Gap, Aisle-by-aisle, Combined/Combined+ heuristics. In this study, we consider the order picking problem of a merchandising company. The objective of the company is to minimize total travelled distance during order picking which leads to an increase in throughput (the number of picks per time). The warehouse under consideration can be said to be non-traditional rectangular due to its block and aisle configuration. Therefore, order picking heuristics, which are proposed for traditional rectangular warehouses, cannot be directly implemented. Accordingly, we modified popular picker routing heuristics to apply for the non-traditional rectangular warehouse layout. Then, a meta-heuristic algorithm is implemented to obtain the best picking sequence of items and order picking route. Finally, we examined the impact of different storage assignment policies on total travelled distance.KeywordsOrder pickingPicker routingWarehouseRouting heuristicMeta-heuristic algorithmStorage assignment

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