Supply Chain Design Based on Two-Stage Mean-CVaR Stochastic Programming with the Possibility of Equipping Suppliers in Disruption

Location-allocation in a supply chain is a strategic level decision due to high cost, impossibility of change and the scope of its impact on other decisions and activities, and the selection of suppliers and production and transportation policies is at a tactical level. Integrating different levels of supply chain decisions helps overall costs reduction and performance improvement. To this end, in this paper, a two-stage mean-conditional value at risk model is used to allocate locations and calculate the flow of materials and manufactured products of a multi-product-multi-level supply chain. In this model, distributors and suppliers face the possibility of disruption, and to prevent disruption on the side of suppliers, they can be equipped by spending additional costs. Sources of uncertainty in the model include shipping costs, end-user demand, and the possibility of disruption to distribution centers and suppliers. The research model uses the conditional value at risk along with the risk aversion factor to control the risk of long distances. The designed model is eventually transformed into a single-level linear programming with the help of Monte Carlo simulation. At the end, while solving a numerical example, the model is implemented and the related sensitivity analysis is presented.</em>