Supplier Selection and Order Allocation Planning Under Political and Disruption Risks

Nowadays, global supply chains are more prone to disruption risks than before, in this regard both practitioners and academics has recognized the need of accounting for resilience. Accordingly, in this paper we present a multi-objective mixed possibilistic, two-stage scenario-based stochastic programming model to handle supplier selection and order allocation problem in a global supply chain under operational and disruption risks. The original model encompasses two minimization objectives for cost and political risk, and one maximization objective function for resilience of the supply base. A comprehensive solution method is developed to solve the presented model efficiently. The proposed model is evaluated via computational experiments.