Optimizing profit and reliability using a bi-objective mathematical model for oil and gas supply chain under disruption risks

Abstract

Today, oil and natural gas are the most important sources of human energy. These two essential sources have strategic importance in economic and political equations of the world and can play a significant role in the process of international relations. To this end, this research design a multi-echelon network for the oil and gas supply chain includes extraction, purification, storage and shipping to the target market. Furthermore, a bi-objective mathematical model is formulated which attempts to maximize total profit from the sale of fossil fuels and to maximize the reliability of processing plants to meet the applicants’ demand. Besides, there may be disturbances in the extraction phase due to the failure of the extractors. To this end, several disruption scenarios are provided to deal with possible disorders. Moreover, a real-world case study in the Iranian oil and gas industry is applied to verify the proposed model and it is solved using augmented ε-constraint and goal programming methods. Also, the sensitivity analysis is performed to provide some useful managerial insights. The results show that the ε-constraint method was selected as the best approach in terms of CPU time and objective functions’ values. Moreover, an increment in demand led to the use of more gathering centers, which increased the inventories and economic factors such as costs. Likewise, shipping costs of products to gathering centers are also very effective in selecting them. Therefore, locating gathering centers is a very important and precise task that is affected by geographical conditions, transport equipment, and proximity to key applicants.