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A Novel Solution Approach to a Priority-Slot-Based Continuous-Time Mixed Integer Nonlinear Programming Formulation for a Crude-Oil Scheduling Problem

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journal contribution
posted on 22.09.2016, 00:00 by Yuming Zhao, Naiqi Wu, Zhiwu Li, Ting Qu
To satisfy component concentration constraints in crude oil operations, it is necessary to blend different oil types, resulting in a mixed integer nonlinear programming (MINLP) formulation for the scheduling problem of crude oil operations. Because of the intractability of such a nonlinear problem, approximate methods were proposed in the literature. However, by the existing methods, a composition concentration discrepancy may occur, leading to an infeasible solution; or a feasible solution cannot be found even if such a solution exists for some cases. Based on a priority-slot modeling method, this paper copes with the crude-oil scheduling problem suffering from composition concentration discrepancy. To find a solution without composition concentration discrepancy, a valid inequality is added to the MINLP model. Also, the model size is significantly reduced by properly determining the number of slots. Then, a novel solution method is proposed. By this method, the problem is iteratively solved and, at each iteration step, only a reduced 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 are done to test the performance of the proposed method. Results show that the proposed method outperforms the existing ones.