Pipelines provide an economic fluid transportation mode for petroleum systems, especially when large amounts of petroleum derivatives have to be pumped for long distances. The system reported in this paper is composed by an oil refinery, one multiproduct pipeline connected to several depots and to the local consumer markets that receive large amounts of oil products. Extensive distances must be covered to reach the depots and the pipeline operates intermittently due to periodic increases in energy costs. The pipeline is divided into segments that connect two consecutive depots and packs that contain one product that compose the segments. Mixed-integer linear programming optimization models that are generated from linear disjunctions and rely on discrete time are proposed for the scheduling system. In the first model it is assumed that the pipeline is divided into packs of equal size, whereas the second one relaxes such assumption. Key decisions of this model involve loading and unloading operations of tanks and of the pipeline These models satisfy all operational constraints, such as mass balances, distribution constraints, product demands, sequencing constraints and logical constraints for pipeline operation. Results generated include the inventory levels at all locations, the distribution of products among the depots and the best ordering of products in the pipeline. Two examples are solved, including a real-world system that is composed of five depots and distributes gasoline, diesel, liquefied petroleum gas and jet fuel for a 3-day time horizon. (C) 2003 Elsevier Science Ltd. All rights reserved.