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Complementarity-based nonlinear programming techniques for optimal mixing in gas networks. (English) Zbl 1431.90017
Summary: We consider nonlinear and nonsmooth mixing aspects in gas transport optimization problems. As mixed-integer reformulations of pooling-type mixing models already render small-size instances computationally intractable, we investigate the applicability of smooth nonlinear programming techniques for equivalent complementarity-based reformulations. Based on recent results for remodeling piecewise affine constraints using an inverse parametric quadratic programming approach, we show that classical stationarity concepts are meaningful for the resulting complementarity-based reformulation of the mixing equations. Further, we investigate in a numerical study the performance of this reformulation compared to a more compact complementarity-based one that does not feature such beneficial regularity properties. All computations are performed on publicly available data of real-world size problem instances from steady-state gas transport.

90B06 Transportation, logistics and supply chain management
90C20 Quadratic programming
90C11 Mixed integer programming
90C30 Nonlinear programming
Full Text: DOI
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