This paper presents a mixed-integer linear programming (MILP) model with a continuous time representation to address the Tank Farm Operation Problem (TFOP) of finished products in refineries. Real scenarios are considered, which were obtained from the planning of refineries and the external pipeline network scheduling, proposed by Ind. Eng. Chem. Res. 2010, 49, 5661. The developed MILP model determines the scheduling of loading and unloading operations in the tank farm of finished products at each refinery, but is subjected to time-window constraints. A decomposition approach has been applied, and multi-product scenarios proposed by Ind. Eng. Chem. Res. 2010, 49, 5661 were broken in single product scenarios. Each one of these scenarios is related with the tank farm in a specific refinery. Therefore, they are presenting volumes and values of stored inventories, maximum capacity tanks, and start and end times to product movements at the refinery interfaces (production, demand, and pipelines). The proposed MILP model searches a scheduling that minimizes the movements within the refinery tank farm in order to respect the imposed operational and structural constraints. Further, for making feasible the scheduling in a smaller computational time, an iterative algorithm is developed and a new model approach, named MILP-IA, is added within the solution process. The results allow us to analyze the model computational time, the temporal and structural violations, and the number of product movements for each scenario. For the studied cases, we can also check for attending to time and monthly volume constraints for each interface. Finally, the results also indicate that the proposed MILP-IA approach finds solutions in computational times on the order of minutes. The obtained solutions contribute to improve the transfer and storage activities (TS) on two main points: (i) they minimize the number of movements, facilitating the plant operational tasks (searching for routes); and (ii) they provide feedback to the pipeline scheduling, creating a collaborative integration between refinery subsystems, linking all information about internal and external product movements at refineries.