A stochastic linear programming method for the reliable oil products supply chain system with hub disruption

Abstract

This paper focuses on a reliable design of oil products supply chain system, which is conductive to promote the sales of oil products. A multi-scenario MILP (Mixed Integer Linear Programming) model coupled with Monte Carlo sampling is employed for optimizing the supply chain system with considering the transportation process of oil products, the stochastic hub disruption and the demand uncertainty. A real-world case is presented to illustrate the accuracy, applicability and efficiency of the proposed model. High-quality solutions are obtained successfully under deterministic conditions as well as uncertain conditions. Then, the effect of uncertainties on the supply chain system design is also analyzed. Finally, the results demonstrate that the stability and flexibility of the designed supply chain system could be substantially improved with less extra costs.