Hierarchical Decomposition Approach for Crude Oil Scheduling: A SINOPEC Case

This work addresses the large-scale crude oil scheduling problem of China’s SINOPEC Maoming refinery that imports various types of crude oil from two terminals via bidirectional long-distance pipelines. We use a hierarchical decomposition approach to construct a two-stage model of the refinery operations. In the upper-level model, storage and charging tanks are aggregated to determine the inflows and outflows between the two terminals and the refinery plant. The lower-level submodels solve the detailed loading and unloading operations at storage and charging tanks inside the terminals and the refinery plant. To further improve the computational efficiency, we develop a rule-based tank-selection strategy to obtain a feasible schedule. Although state-of-the-art commercial solvers cannot obtain feasible solutions of the relaxed monolithic mixed-integer linear programming model within a reasonable time, our decomposition heuristic can generate schedules that are more flexible than manually generated schedules. It also provides the refinery with annual estimated cost savings of $30 million.