Design of a sustainable integrated crude oil manufacturing network with risk cover and uncertainty considerations: a case study

The oil industry is one of the largest and most influential manufacturing systems in the world. In addition to being the world's leading source of energy, oil plays an important role in determining the national power and international reputation of various countries. This industry has certain characteristics that distinguish it from other manufacturing systems. Some of these characteristics include the strategic importance of products, variable prices, and political pressure. This industry is one of the most sophisticated manufacturing systems in the world, incorporating integrated activities from vendor to customer. In this paper, we presented a multi-objective integrated mathematical model including all three upstream, midstream, and downstream sectors of the crude oil supply chain. Our proposed multi-product, multi-period, and multi-objective mixed-integer linear programming model address an optimal solution. We have a scenario-based approach which deals with two sources of uncertainty. Conditional value at risk approach was applied to minimize the risk. Also, the social and environmental aspects of the supply chain are considered simultaneously to propose a sustainable model. Finally, the performance of the model is illustrated and analyzed using the real data of a national refining and distribution company. According to the results, the risk coverage by conditional value at risk has a positive impact on the model.