Multimodal Fuzzy Downstream Petroleum Supply Chain: A Novel Pentagonal Fuzzy Optimization

The petroleum industry has a complex, inflexible and challenging supply chain (SC) that impacts both the national economy as well people’s daily lives with range of services, including transportation, heating, electricity, lubricants, chemicals petrochemicals. In industry, management presents several challenges, especially in logistics sector, are not found other industries. addition, logistical challenges contribute significantly to cost oil. Uncertainty regarding customer demand affects SC networks. Hence, flexibility can be maintained by addressing uncertainty. On hand, real world, decision-making often ambiguous or vague. some cases, measurements incorrect owing measurement errors, instrument faults, etc., which lead pentagonal fuzzy number (PFN) is extension number. Therefore, it necessary develop quantitative models optimize operations This study proposed linear programming model under an uncertain environment. minimizes along refineries, depots, multimode transport nodes. Further developed optimization, alternative approach solve downstream using mixed-integer (MILP) obtain feasible solution transportation problem. this model, coefficient costs parameters assumed Furthermore, defuzzification performed accuracy function. To validate technique feasibility solution, illustrative example oil gas considered, providing improved results compared existing techniques demonstrating its ability benefit companies objective study.