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. (C) 2019 Elsevier Ltd. All rights reserved.

Automated summary

This paper introduces a new optimal scheduling model for an oil transportation system, which can avoid forbidden product sequences, consider filler batch constraints, and include inventory management constraints. The model shows excellent performance in computational efficiency and linear programming, making a significant contribution to the existing technology.