Complementarity-Based Nonlinear Programming Techniques for Optimal Mixing in Gas Networks

Hante F, Schmidt M (2017)


Publication Language: English

Publication Type: Other publication type

Publication year: 2017

URI: http://www.optimization-online.org/DB_HTML/2017/09/6198.html

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.

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How to cite

APA:

Hante, F., & Schmidt, M. (2017). Complementarity-Based Nonlinear Programming Techniques for Optimal Mixing in Gas Networks.

MLA:

Hante, Falk, and Martin Schmidt. Complementarity-Based Nonlinear Programming Techniques for Optimal Mixing in Gas Networks. 2017.

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