Scenario-based stochastic model for supplier selection and order allocation under disruption risk and quantity discount

Abstract

In this paper, we develop two stochastic mixed integers linear programming (SMILP) models for supplier selection under disruption risk considering different capacity, failure probability, uncertain demand and quantity discounts. The suppliers are assumed domestic suppliers and global suppliers. The obtained combinatorial stochastic optimisation problem is formulated as a mixed integer program with conditional value-at-risk technique (CVaR). Numerical examples and computational results are presented. The proposed models can optimise the present problem through an estimated value at risk (VaR) and minimised CVaR simultaneously. The computational results reveal that the proposed models allow the decision maker to make an efficient selection of suppliers under disruption risk. Results also show that the decisions are not univocal because they depend on the risk proneness of the decision maker.