A holistic MILP model for scheduling and inventory management of a multiproduct oil distribution system

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 linear programming (MILP) model that is designed based on real-world necessities and that requires significantly fewer binary variables than previous work. As main contributions, the model: i) can rigorously avoid forbidden product sequences in every pipeline segment; ii) considers filler batch constraints to avoid large contamination volumes; and iii) includes inventory management constraints in the different pipeline nodes. We first use an illustrative example before testing the approach with a new large-scale example problem and three real-world cases from the literature. Results show that the proposed model has a tight linear programming (LP) relaxation and is very efficient computationally. It is thus a significant contribution to the state-of-the-art.