Order picking is the most labor cost consuming element in warehouse operations. In this paper, we consider an order picking process in a single picking aisle in the forward pick area, consisting of multiple locations (pick faces). The picking is performed by a group of pickers, each characterized by stochastic (forward and backward) walking process and picking times. We assume that the bucket brigade (BB) approach is applied, in a static environment, in which a given set of orders has to be picked. In order to improve the picking process, we suggest a batching procedure, where the objective is to minimize the total picking time, namely, the makespan. The proposed batching approach has two advantages: (1) it decreases the total travel time, since the items can be picked in a reduced number of picking tours as compared with picking each order separately; and (2) it balances the picking load along the picking aisle, consequently reducing the blockage occurrences. We model the problem as a Constraint Programming (CP) formulation, which was shown to be efficient in providing high quality solutions for non-linear models. Small and large scale examples are given to demonstrate the proposed approach, where the former consists of 24 orders, which are picked in five locations (pick faces), and the latter consists of 50 orders, which are picked in 12 locations. The solution obtained by the CP formulation is compared via simulation with an order by order picking and with a naïve batching approach, in which orders are batched in an arbitrary sequence until approaching the available capacity.
Progress in Material Handling Research
Bukchin, Yossi; Hanany, Eran; and Khmelnitsky, Eugene, "Batching in Bucket Brigade Order Picking" (2018). 15th IMHRC Proceedings (Savannah, Georgia. USA – 2018). 10.