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. (C) 2003 Elsevier Ltd. All rights reserved.
integer programming scheduling pipeline optimisation decision support systems