Solving Heated Oil Pipeline Problems Via Mixed Integer Nonlinear Programming Approach
Abstract: It is a crucial problem how to heat oil and save running cost for crude oil transport. This paper strictly formulates such a heated oil pipeline problem as a mixed integer nonlinear programming model. Nonconvex and convex continuous relaxations of the model are proposed, which are proved to be equivalent under some suitable conditions. Meanwhile, we provide a preprocessing procedure to guarantee these conditions. Therefore we are able to design a branch-and-bound algorithm for solving the mixed integer nonlinear programming model to global optimality. To make the branch-and-bound algorithm more efficient, an outer approximation method is proposed as well as the technique of warm start is used. The numerical experiments with a real heated oil pipeline problem show that our algorithm achieves a better scheme and can save 6.83% running cost compared with the practical scheme.
Keywords: Heated oil pipeline problem, MINLP, Nonconvex relaxation, Convex relaxation, Branch-and-bound, Outer approximation, Warm start.
Category 1: Applications -- OR and Management Sciences
Category 2: Integer Programming ((Mixed) Integer Nonlinear Programming )
Citation: arXiv:1907.10812 [math.OC] 25 Jul 2019, https://arxiv.org/abs/1907.10812
Entry Submitted: 07/26/2019
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