Complementarity-based nonlinear programming techniques for optimal mixing in gas networks

Falk M. Hante and Martin Schmidt ()
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Falk M. Hante: Friedrich-Alexander-Universität Erlangen-Nürnberg
Martin Schmidt: Trier University

EURO Journal on Computational Optimization, 2019, vol. 7, issue 3, No 4, 299-323

Abstract: Abstract 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.

Keywords: Gas transport networks; Mixing; Inverse parametric quadratic programming; Complementarity constraints; MPCC; 90-08; 90C11; 90C33; 90C35; 90C90 (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s13675-019-00112-w

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