A New MILP Model for Supplier Selection: Improving Efficiency and Solution Quality under Risk

This paper contributes to the field of supplier selection under risk by proposing a Mixed Integer Linear Programming (MILP) model that integrates key decisionmaking factors such as cost and risk mitigation strategies. The proposed model offers a comprehensive approach for selecting the best supplier portfolio under uncertainty. Furthermore, the paper provides a detailed comparison of the proposed MILP model with an existing model from the literature, highlighting its advantages in terms of solution quality and computational efficiency. The results of the comparison demonstrate that the proposed approach outperforms the benchmark model. This work advances the literature on supplier selection under uncertainty by introducing a novel, practical, and more effective optimization approach that can be applied across
various industries to enhance decision-making processes.