Designing an efficient multi-objective mathematical model to choose the best strategy for critical investment risks in oil and gas projects

Document Type : Research Paper


1 Department of Industrial Management, Rasht Branch, Islamic Azad University, Rasht, Iran

2 Department of Accounting, Roudsar and Amlash Branch, Islamic Azad University, Roudsar, Iran

3 Department of Industrial Engineering, Sari Branch, Islamic Azad University, Sari, Iran


According to the conducted research, oil and gas industry projects have many complexities and uncertainties, and investment in these projects is associated with high risks. In this research, while identifying the most critical risks that have an impact on investing in oil and gas projects, they have been identified in the first place. Then, the importance of each of the specified criteria is determined. To achieve the aforementioned goals, modern computing methods have been used. In the phase of identifying factors from fuzzy Delphi; In the importance and prioritization stage, multi-criteria decision-making methods are used, and in the allocation stage, multi-objective mathematical modeling is used. Therefore, first, a list of 21 investment risks in industry and gas was collected by reviewing the literature and research backgrounds. The collected risks were refined and finalized using the fuzzy Delphi approach. Finally, the risks of sanctions by an institution or country, liquidity, health risks (such as the corona epidemic), financial potential, exchange rate fluctuations, and sudden changes in inflation as risks. considered in this research. Then, considering factors such as quality, cost, technology, time, and information preparation as indicators influencing the occurrence of considered risks, their importance has been determined using the best-worst method. According to the weight calculated for each of these factors, respectively equal to 0.23; 0.09; 0.52; 0.07, and 0.09 are estimated. Then, according to the importance obtained by using the GRA-VIKOR approach, the risk ranking was determined by considering the factors affecting them. Finally, by using the three-objective linear programming model with the objectives of maximizing the level of quality, minimizing cost and time, and solving it using the epsilon-constraint method, an appropriate response strategy is determined for each of the considered investment risks.


Main Subjects

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