A mixed-integer linear programming-based scheduling model for refined-oil shipping

The refined oil transportation problem investigated in this paper lies on the intersection of the scheduling and routing of tramp shipping and the petroleum supply chain, with unprecedented large-scale and complex rules. Two mixed-integer linear programming formulations are developed for the assignment between tasks, vessels, and timing issues. The first model uses a time-slot concept under a continuous-time representation, where the constraints that deal with vessel assignment, capacity, timing, demand, and slack stock control are considered. The second model uses a discrete-time representation with time assignment, portal counting, and strict stock control constraints. By virtue of the data collected from an oil company, this modeling approach is validated and used to generate feasible scheduling solutions with lower costs than are currently achieved in the real situation. Finally, the impact of the model parameters is analyzed under different optimization scenarios.