Abstract
The problem of assembling a large number of heterogeneous time-critical customer orders from a wide range of products is one of the biggest challenges that E-commerce retailers are currently facing. Unlike the traditional warehouses that could hardly keep up with the surge in demands brought by the e-commerce boom, internet fulfillment warehouses (IFWs) are designed to suit such a fast-paced environment for handling sales and customer orders of online retailers, and scattered storage is one of the trending storage assignment strategies adopted by many of them. Under the scattered storage strategy, the newly arrived items are exploded into a bunch of small stocking lots and purposely scattered around the entire warehouse. Such an assignment strategy enhances the probability of always having a nearby location containing the requested item. Thus, it potentially shrinks the order fulfillment time. This paper presents a novel scattered storage assignment approach suited for IFWs operations. Compared with the existing literature, this assignment approach pays more attention to handling the inevitable quantity fluctuation of customer ordering patterns. The proposed problem is mathematically expressed as a MIP model, and a heuristic algorithm, consisting of a feasibility checking procedure and a two-stage item allocation procedure, is developed to generate a high-quality solution in a time-efficient manner. Numerical studies are then conducted to assess the computational performance of the proposed algorithm and to justify if the proposed model is efficacious and improves order-picking efficiency.
Published Version
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