Pipelines have been proved to be an efficient and economic way to transport oil products. However, the determination of the scheduling of operational activities in pipeline networks is a difficult task, and efficient methods to solve such complex problem are required. In this contribution, a real-world pipeline network is studied, and an optimization model is proposed in order to address the network scheduling activities. A hierarchical approach is proposed on the basis of the integration of a mixed integer linear programming (MILP) model and a set of heuristic modules. This article exploits the MILP model, the main goal of which is to determine the exact time instants that products should be pumped into the pipelines and received in the operational areas. These time instants must satisfy the pipeline network management and operational constraints for a predefined planning period. Such operational constraints include pipeline stoppages, movement of batches through many areas/pipelines, use of preferential routes to avoid contamination losses, on-peak demand hours of pumping, local constraints, reversions of flow direction, and surge tank operations, while satisfying a series of production/consumption requirements. The developed continuous-time model is applied to a large real-world pipeline system, where more than 14 oil derivatives and ethanol are transported and distributed between supply and demand nodes.