New model of the storage location assignment problem considering demand correlation pattern

Abstract Order-picking is the most time- and labor-consuming operation in a warehouse and significantly influences supply chain efficiency. One of the basic methods for improving order-picking efficiency involves assigning storage locations to appropriate items, i.e., the storage location assignment problem (SLAP). In existing studies, most storage assignment methods only consider the properties of individual item rather than the item groups that are usually collectively required. This paper introduces the concept of the demand correlation pattern (DCP) to describe the correlation among items, based on which a new model is constructed to address the SLAP. The model is subsequently reduced using the S-shape routing strategy, and a method for determining DCPs from historical data is proposed. To solve the model, a heuristic and a simulated annealing method are developed. The proposed methods are examined and compared extant methods using both real data collected from an online retailer and numerical instances that are randomly generated. The computational results are discussed.

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