In the oil supply chain, products transportation by pipelines is the most used distribution modal, justified by its high volume capacity, reliability, and safety compared to the other transportation modes. The scheduling of pumping and delivery operations in pipelines is a complex problem. Thus, a better usage of the involved resources calls for the existence of tools that can help the associated decision-making process. This work explores this need and proposes a decomposition approach that integrates Mixed Integer Linear Programming models and heuristics to solve the scheduling of a single-source and multiple distribution centers (DCs) pipeline network, where a repumping DC operation, not yet considered in the literature in the area, is often used in practice. This operation corresponds to a situation where the repumping DC acts as the final DC of the network, receiving all batches arriving and, at the same time, operates as a source node. The DC repumps products previously received in tanks to attend the demand of downstream DCs. In this case, the storage profile has to be carefully controlled in order to perfectly manage the involved operations. A real-world Brazilian network, where such operation can be executed for the transport into the last segment, is used to validate the proposed approach. The approach solves the case where the repumping DC attends a single downstream destination. Scheduling results with and without the repumping operation active are presented. The obtained results translate valid operational solutions in a reasonable CPU time for both executions.