Complementarity-Based Nonlinear Programming Techniques for Optimal Mixing in Gas Networks
- 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.
MetadatenAuthor: | Falk Hante, Martin Schmidt |
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Parent Title (German): | EURO Journal on Computational Optimization |
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Document Type: | Article |
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Language: | English |
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Date of Publication (online): | 2017/09/12 |
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Date of first Publication: | 2017/09/12 |
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Release Date: | 2017/09/12 |
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Tag: | Complementarity constraints; Gas transport networks; Inverse parametric quadratic programming; MPCC; Mixing |
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Issue: | 7(3) |
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Page Number: | 25 |
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First Page: | 299 |
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Last Page: | 323 |
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Institutes: | Friedrich-Alexander-Universität Erlangen-Nürnberg |
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Subprojects: | A03 |
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| B08 |
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