Optimization under uncertainty of the integrated oil supply chain using stochastic and robust programming

This paper proposes the development of a strategic planning model for an integrated oil chain considering three sources of uncertainty: crude oil production, demand for refined products and market prices. To deal with these uncertainties, three formulations are proposed: (1) a two-stage stochastic model with a finite number of realizations, (2) a robust min–max regret model and (3) a max–min model. These models were applied to Brazil's oil chain, comprising 17 refineries and three main petrochemical plants, 16 groups of crude oils, 50 intermediate products, 10 final products, 13 terminals and a logistic network composed of 278 transportation arcs relative to the road, water, rail and pipeline modes. The time horizon analyzed covers 10 years. The results indicate significant financial differences between the three formulations, depending on the agent's risk profile.