A mixed integer programming approach for scheduling commodities in a pipeline

This paper addresses the problem of developing an optimisation structure to aid the operational decision-making of scheduling activities in a real-world pipeline scenario. The pipeline connects an inland refinery to a harbour, conveying different types of oil derivatives. The optimisation structure is developed based on mixed integer linear programming (MILP) with uniform time discretisation, but the MILP well-known computational burden is avoided by the proposed decomposition strategy, which relies on an auxiliary routine to determine temporal constraints, two MILP models, and a database. The scheduling of operational activities takes into account product availability, tankage constraints, pumping sequencing, flow rate determination, and a variety of operational requirements. The optimisation structure main task is to predict the pipeline operation during a limited scheduling horizon, providing low cost operational procedures. Illustrative instances demonstrate that the optimisation structure is able to define new operational points to the pipeline system, providing significant cost saving.