A Multi-Objective Supply Chain Configuration for the Oil Industry under Uncertainty

In recent years, supply chains have become an attractive topic for managers and industrialists, and the life and death of organizations and businesses somehow depend on the activity of intertwined chains. On the other hand, in today's highly competitive environment, the high speed of change and evolution has increased the uncertainty and ambiguity of decisions, which makes it difficult to predict future conditions in supply chains. Therefore, reliable planning should be done in uncertain and ambiguous conditions for better and more accurate planning. One of the new and reliable approaches is the robust programming approach. In this study, transferring petroleum products from supply points to consumption areas is examined through a supply chain. Due to the uncertainty in the product demand, a mathematical model is used with two objectives including the reduction of shipping costs and the reduction of the number of loads. Due to the high volume of calculations and the problem data as well as the lack of ability to use exact solution methods, especially on a large scale, PSO and MOGA-II meta-heuristic algorithms are used to solve the proposed model. The results show that the model has the required efficiency in large dimensions and the proposed solution methods provide appropriate answers.