Abstract
This study proposes a joint order batching and depot selecting model (JOBDS) in narrow-aisle order picking systems (OPSs). The two depots in a hypothetical narrow-aisle OPS distribute the operational burden imposed by inspectidon and packaging. We build an order batching model and develop a mixed integer programming (MIP) algorithm considering the travel distance to each depot’s location for a 48-order and a 72-order case. We also develop large-scale heuristic algorithms: Seed and Saving algorithms. A comparison to order batching model with single depot (OBSD) shows that the proposed algorithms shorten the travel distance on average 4.19 ~ 13.38%. We provide additional simulation studies to analyze total travel time by walk speed, order size, inspection and packaging times, number of pickers, and location of depots. Consistently, travel time in JOBDS is operationally advantageous compared to OBSD.
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