Habeck, Oliver ; Pfetsch, Marc E. (2024)
Combinatorial acyclicity models for potential‐based flows.
In: Networks, 2021, 79 (1)
doi: 10.26083/tuprints-00020137
Artikel, Zweitveröffentlichung, Verlagsversion
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Kurzbeschreibung (Abstract)
Potential‐based flows constitute a basic model to represent physical behavior in networks. Under natural assumptions, the flow in such networks must be acyclic. The goal of this article is to exploit this property for the solution of corresponding optimization problems. To this end, we introduce several combinatorial models for acyclic flows, based on binary variables for flow directions. We compare these models and introduce a particular model that tries to capture acyclicity together with the supply/demand behavior. We analyze properties of this model, including variable fixing rules. Our computational results show that the usage of the corresponding constraints speeds up solution times by about a factor of 3 on average and a speed‐up of a factor of almost 5 for the time to prove optimality.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2024 |
| Autor(en): | Habeck, Oliver ; Pfetsch, Marc E. |
| Art des Eintrags: | Zweitveröffentlichung |
| Titel: | Combinatorial acyclicity models for potential‐based flows |
| Sprache: | Englisch |
| Publikationsjahr: | 13 Februar 2024 |
| Ort: | Darmstadt |
| Publikationsdatum der Erstveröffentlichung: | 2021 |
| Ort der Erstveröffentlichung: | New York |
| Verlag: | Wiley |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | Networks |
| Jahrgang/Volume einer Zeitschrift: | 79 |
| (Heft-)Nummer: | 1 |
| DOI: | 10.26083/tuprints-00020137 |
| URL / URN: | https://tuprints.ulb.tu-darmstadt.de/20137 |
| Zugehörige Links: | |
| Herkunft: | Zweitveröffentlichung DeepGreen |
| Kurzbeschreibung (Abstract): | Potential‐based flows constitute a basic model to represent physical behavior in networks. Under natural assumptions, the flow in such networks must be acyclic. The goal of this article is to exploit this property for the solution of corresponding optimization problems. To this end, we introduce several combinatorial models for acyclic flows, based on binary variables for flow directions. We compare these models and introduce a particular model that tries to capture acyclicity together with the supply/demand behavior. We analyze properties of this model, including variable fixing rules. Our computational results show that the usage of the corresponding constraints speeds up solution times by about a factor of 3 on average and a speed‐up of a factor of almost 5 for the time to prove optimality. |
| Freie Schlagworte: | acyclic flows, gas networks, mixed‐integer program, network optimization, potential‐based flows, valid inequalities |
| Status: | Verlagsversion |
| URN: | urn:nbn:de:tuda-tuprints-201379 |
| Sachgruppe der Dewey Dezimalklassifikatin (DDC): | 500 Naturwissenschaften und Mathematik > 510 Mathematik |
| Fachbereich(e)/-gebiet(e): | 04 Fachbereich Mathematik 04 Fachbereich Mathematik > Optimierung |
| Hinterlegungsdatum: | 13 Feb 2024 10:30 |
| Letzte Änderung: | 15 Feb 2024 14:02 |
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| Suche nach Titel in: | TUfind oder in Google |
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- Combinatorial acyclicity models for potential‐based flows. (deposited 13 Feb 2024 10:30) [Gegenwärtig angezeigt]
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