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EN
This paper introduces the problem of designing a single-product supply chain network in an agile manufacturing setting under a vendor managed inventory (VMI) strategy to seize a new market oppor-tunity. The problem addresses the level of risk aversion of the retailer when dealing with the uncertainty of market related information through a conditional value at risk (CVaR) approach. This approach leads to a bilevel programming problem. The Karush–Kuhn–Tucker (KKT) conditions are employed to trans-form the model into a single-level, mixed-integer linear programming problem by considering some relaxations. Since realizations of imprecisely known parameters are the only information available, a data-driven approach is employed as a suitable, more practical, methodology of avoiding distribu-tional assumptions. Finally, the effectiveness of the proposed model is demonstrated through a numer-ical example.
EN
This paper aims to develop an inventory model considering discrete demand, coordinated pricing, and multiple delivery policy in a single-buyer single-supplier production-inventory system. The shortage is not allowed and the planning horizon is considered to be infinite. The main objective of the framework is to equip the decision-maker with optimal order, pricing, and shipment quantities to maximize the total profit of the system. The results obtained from the numerical example reveal that the proposed approach with an average selling price equal to about 94% of the classical model, has resulted in an average profit increase of about 16% and an average order increase of about 34% compared to the classical approach.
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