This paper addresses the optimal scheduling of an oil transportation system characterized by a straight multiproduct pipeline featuring multiple input and output nodes, where products are dispatched to local markets often by tanker trucks. We present a new continuous-time mixed integer…
Continue Reading
An improvement on the scheduling of pumping and delivery operations in an installed pipeline network can lead to considerable profits to the using companies, such as oil companies. This paper proposes a decomposition approach that integrates heuristic procedures and mixed integer linear programming…
Continue Reading
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…
Continue ReadingThis paper proposes a decomposition approach combining heuristic algorithms and Mixed Integer Linear Programming (MILP) models to solve the long-term scheduling of a multiproduct pipeline connecting a single-source to multiple distribution centers. The solution considers many operational…
Continue Reading
The manufacturing of pharmaceutical products is preceded by complex development phases where process design, planning, and scheduling problems must be considered as deeply linked, fact that has not yet been adequately handled by the existing literature. In this perspective, this work discusses the…
Continue Reading
Pipelines play an important role in the oil supply chain linking different supply chain echelons and acting as one of the most sustainable, safe economical transportation mode. In this context, multiproduct pipeline scheduling is a key issue to be addressed in an optimized form, namely when…
Continue ReadingWhether you are looking for a research group to support you on your research topic or you have a difficult problem to solve, contact us and possibly start a collaboration
Contact us