One of the most essential elements needed by humans to carry out their tasks is transportation. It also sees as one of the most crucial elements for economic growth. Since operations research applications play a major role in the decision-making process on a scientific basis for planning productive and economical projects, they are interested in determining the best plan for transportation at the lowest costs from their production sources to their requesting bodies to arrive at the optimal decision. The problem of oil product transportation inside the Midland Oil Company has been the focus of this research in order to achieve this goal. As a result, in this work, fuzzy theory and a contemporary algorithm (ATM) were used to investigate whether adopting transport models could effectively lower the transportation costs of oil products in production institutions. When compared to utilizing a ready application (Win QSB), the approach used by the Midland Oil Company to distribute its oil products from its four main warehouses to the provinces that have contracts with the company is more effective at handling fuzzy data. The approaches employed to address the issue are the best ones for moving the product at the lowest possible cost, as shown by the findings Additionally, a number of recommendations and ideas have been made in light of the study' findings in order to assist in utilizing the solution techniques' contribution to decision-makers' ability to make decisions.