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

Beitrag in einer Fachzeitschrift


Details zur Publikation

Autorinnen und Autoren: Hante F, Schmidt M
Zeitschrift: EURO Journal on Computational Optimization
Jahr der Veröffentlichung: 2019
ISSN: 2192-4406
eISSN: 2192-4414


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.


FAU-Autorinnen und Autoren / FAU-Herausgeberinnen und Herausgeber

Hante, Falk PD Dr.
Lehrstuhl für Angewandte Mathematik


Einrichtungen weiterer Autorinnen und Autoren

Universität Trier


Zitierweisen

APA:
Hante, F., & Schmidt, M. (2019). Complementarity-based nonlinear programming techniques for optimal mixing in gas networks. EURO Journal on Computational Optimization. https://dx.doi.org/10.1007/s13675-019-00112-w

MLA:
Hante, Falk, and Martin Schmidt. "Complementarity-based nonlinear programming techniques for optimal mixing in gas networks." EURO Journal on Computational Optimization (2019).

BibTeX: 

Zuletzt aktualisiert 2019-21-06 um 08:32