A trio of resiliency, reliability, and uncertainty to design and plan the downstream oil supply chain

The main goal of this research is to design and plan a downstream oil supply chain network under mixed uncertainty. To reach this goal, a bi-objective mixed-integer linear model is proposed to make decisions at tactical and strategic levels. Notably, to deal with mixed uncertainty, a hybrid uncertain programming approach including adjustable possibilistic programming, chance-constrained programming, scenario-based programming, and p-robust optimization is developed and applied. Finally, the proposed model is implemented in a real-life case from the National Iranian Oil Products Distribution Company to illustrate the applicability and efficacy of the proposed approach. The analysis of the results indicates that the benefit of the used methods leads to the improvement of network performance against operational and disruption risks. Moreover, the analysis of the results indicates that the tailored approaches improve the total costs, the resiliency of the network, and the reliability of the chain in comparison to the deterministic situation.

Automated summary

The research aims to design and plan a downstream oil supply chain network under mixed uncertainty. A bi-objective mixed-integer linear model is proposed to make decisions at tactical and strategic levels. To deal with mixed uncertainty, a hybrid uncertain programming approach is developed and applied. The implementation of the proposed model in a real-life case leads to improved network performance and cost reduction against operational and disruption risks.