A Novel Solution Approach To Scheduling Of Crude-Oil Operations Based On An Improved Continuous-Time Formulation

To satisfy component concentration constraints in crude oil operations, it is necessary to blend different oil types, resulting in a mixed integer non-linear programming (MINLP) formulation for the scheduling problem of crude oil operations. Due to the intractability of such problems, approximate methods are proposed in the literature. However, by the existing methods, either a composition concentration discrepancy may occur, leading to an infeasible solution or a feasible solution cannot be found even if such a solution exists. Based on a priority-slot modeling method, this paper aims to cope with the crude-oil scheduling problem that suffers from composition concentration discrepancy. An MINLP model is improved by adding a valid inequality and the model size is significantly reduced by properly deciding the number of slots. With the obtained formulation, a novel solution method is proposed. By this method, the problem is iteratively solved and, at each iteration step, only a reduced mixed integer linear programming (MILP) problem is solved. Consequently, a solution can be found such that the composition concentration discrepancy is completely eliminated and it is computationally more efficient than the existing ones. Experiments show that the proposed method outperforms the existing ones.