In this paper, we address the construction of a multi-period fashion product supply chain network (FSCN) with the incorporation of production discounts and transportation quantity decisions. A bilevel design framework is proposed to capture the decision-making interaction between a fashion product manufacturer (acting as a leader) and retailers (acting as followers) over multiple periods. By utilizing Karush-Kuhn-Tucker (KKT) conditions, the bilevel optimization model can be transformed into a single-level mixed-integer linear programming (MILP) model. Furthermore, uncertainty in unit transportation cost and demand was addressed via a robust optimization framework, with the aim of balancing the optimal decisions of the upper and lower decision makers. To solve the proposed robust model efficiently, we designed a tailored Benders decomposition (BD) algorithm. To validate the effectiveness of our proposed model and BD algorithm, a case study based on ZARA was conducted. Thus, based on extensive experiments, the benefits of the proposed methods are illustrated, and significant insights are obtained for decision makers.
Citation: Shanshan Gao, Meiyu Liu, Yankui Liu. Constructing a new robust bilevel fashion product supply chain network with uncertain demand and transportation cost[J]. Journal of Industrial and Management Optimization, 2026, 22(4): 2147-2180. doi: 10.3934/jimo.2026079
In this paper, we address the construction of a multi-period fashion product supply chain network (FSCN) with the incorporation of production discounts and transportation quantity decisions. A bilevel design framework is proposed to capture the decision-making interaction between a fashion product manufacturer (acting as a leader) and retailers (acting as followers) over multiple periods. By utilizing Karush-Kuhn-Tucker (KKT) conditions, the bilevel optimization model can be transformed into a single-level mixed-integer linear programming (MILP) model. Furthermore, uncertainty in unit transportation cost and demand was addressed via a robust optimization framework, with the aim of balancing the optimal decisions of the upper and lower decision makers. To solve the proposed robust model efficiently, we designed a tailored Benders decomposition (BD) algorithm. To validate the effectiveness of our proposed model and BD algorithm, a case study based on ZARA was conducted. Thus, based on extensive experiments, the benefits of the proposed methods are illustrated, and significant insights are obtained for decision makers.
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Shanshan Gao, Meiyu Liu, Yankui Liu. Constructing a new robust bilevel fashion product supply chain network with uncertain demand and transportation cost[J]. Journal of Industrial and Management Optimization, 2026, 22(4): 2147-2180. doi: 10.3934/jimo.2026079
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