Abstract
This paper studies the fast-fashion apparel transshipment problem (FATP) among allied retailers. The FATP belongs to the category of practical many–to–many transportation models and has distinct features: the flow out of and the flow into a retailer are restricted by the estimated sales volume in the next time period, the shortage of stock and excess stock for fast-fashion apparel sales all yield penalty costs and the alliance aims to maximize the profit for the retailers as a whole. Therefore, developing an optimal transshipment solution method is important for the alliance. This paper devises mixed-integer linear programming (MILP) models for the FATP. The stock levels, the estimated distribution of sales for the next decision period, the unit penalty costs for a shortage of stock or excess stock and the unit cost of transshipment are parameters that control the flows among retailers. A decision-support system (DSS) was designed based on the model for transshipment management. Experiments were performed to demonstrate the transshipment solutions and reveal the effects of parameters on the solutions for a real-world case. Some tuning methods are designed to assist the decisions of the retailer alliance. The FATP is addressed for fast-fashion apparel sales in the context of an alliance for alleviating the risk of dead stock; the FATP is also a new transportation problem with uncertain supply and demand. The proposed method is a theoretical basis for designing a practical DSS for allied fast-fashion apparel retailers.
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