عنوان مقاله [English]
In this research, a mathematical model of scenario-based mixed integer programming is presented to model the problem of supplier selection and order allocation considering Disruption Risk and Business Volume Discount in a centralized supply chain.The considered supply chain is Bi-Level and contains one manufacturer and several suppliers and as well as There are two categories of suppliers : main suppliers and backup suppliers. As is clear, it is assumed that the unit costs of the main suppliers are lower than those of the backup suppliers.Also It is assumed that the backup supplier supports in disruption conditions if the manufacturer meets the minimum value set by the supplier under normal conditions. Supplier Disruptions are random and independent. It is assumed that the disruption is not due to the lack of raw materials to suppliers. Demand is considered definitive and the model is a single-criteria with the criterion of reducing the cost of all members of the supply chain .Also in the presented model a single-period multi-product supply chain is considered. Due to the importance of supplier selection and high impact of cost of purchasing raw materials on the total cost of the product and its aggravation in the event of disruption, this issue was investigated. Also, by calculating the C-VaR using GAMS and analyzing the sensitivity of the result, We examined the impact of the decision-making risk attitude on the total cost of the supply chain as well as the costs of each member and found out that increasing the decision-maker's sensitivity to risk generally increases the this costs. We also examined this effect on purchases from suppliers. The result was that as the sensitivity to risk increased, the quantities purchased from undisturbed suppliers, whether main or backup, increased, but the quantities purchased from disrupted suppliers decreased. Also, in order to evaluate the efficiency of the model, a case study was conducted in Sapco(Iran Khodro Engineering Design and Parts Supply Company).