Computationally Efficient MILP Model for Scheduling a Branched Multiproduct Pipeline System

This paper presents a novel mixed-integer linear programming (MILP) continuous-time formulation for the detailed scheduling of a branched pipeline system with a single refinery and multiple depots, rigorously accounting for forbidden product sequences in every line. The major advantage against previously published work is that the proposed model allows multiple batches to be processed by a node over a single slot, leading to the requirement of fewer event points to represent a schedule. As one essential key performance indicator in continuous-time models, a lower number of event points brings a significant reduction in computational time. Five benchmark problems from the literature involving different pipeline configurations are tested to validate the superiority of the proposed model. In four of them we were able to find new best solutions.