Abstract
As the e-commerce market has grown rapidly since the coronavirus pandemic, the efficiency of logistics operations has emerged as an important issue. As a way to improve the efficiency of digital picking system (DPS) that handles picking products to fulfill orders, we consider stock keeping unit (SKU) arrangement optimization to reduce the total number of visits to workstations to pack products in totes for a large set of orders. We develop the SKU arrangement optimization model and show that it can be relaxed to be equivalent to multiple-choice knapsack problem (MCKU), which is NP-hard. Recognizing the optimization model cannot be applied in practice, an association-rule-based heuristic algorithm for SKU arrangement is proposed to minimize the number of workstation visits considering variation in the workload among workstations. Under various criteria for SKU selection and arrangement, the heuristic algorithm is shown to significantly reduce the total number of visits not increasing the degree of variation in workstation loads.
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