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GasLib — A Library of Gas Network Instances

Schmidt, Martin ; Aßmann, Denis ; Burlacu, Robert ; Humpola, Jesco ; Joormann, Imke ; Kanelakis, Nikolaos ; Koch, Thorsten ; Oucherif, Djamal ; Pfetsch, Marc E. ; Schewe, Lars ; Schwarz, Robert ; Sirvent, Mathias (2024)
GasLib — A Library of Gas Network Instances.
In: Data, 2017, 2 (4)
doi: 10.26083/tuprints-00016861
Article, Secondary publication, Publisher's Version

Copyright Information: CC BY 4.0 International - Creative Commons, Attribution.

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Item Type: Article
Type of entry: Secondary publication
Title: GasLib — A Library of Gas Network Instances
Language: English
Date: 16 January 2024
Place of Publication: Darmstadt
Year of primary publication: 2017
Place of primary publication: Basel
Publisher: MDPI
Journal or Publication Title: Data
Volume of the journal: 2
Issue Number: 4
Collation: 18 Seiten
DOI: 10.26083/tuprints-00016861
Corresponding Links:
Origin: Secondary publication DeepGreen

The development of mathematical simulation and optimization models and algorithms for solving gas transport problems is an active field of research. In order to test and compare these models and algorithms, gas network instances together with demand data are needed. The goal of GasLib is to provide a set of publicly available gas network instances that can be used by researchers in the field of gas transport. The advantages are that researchers save time by using these instances and that different models and algorithms can be compared on the same specified test sets. The library instances are encoded in an XML (extensible markup language) format. In this paper, we explain this format and present the instances that are available in the library.

Uncontrolled Keywords: gas transport, networks, problem instances, mixed-integer nonlinear optimization, GasLib
Status: Publisher's Version
URN: urn:nbn:de:tuda-tuprints-168610
Additional Information:

Data Set License: CC BY 3.0 Unported (Supplement)

MSC: 90-08; 90C90; 90B10

Classification DDC: 000 Generalities, computers, information > 004 Computer science
500 Science and mathematics > 510 Mathematics
Divisions: 04 Department of Mathematics > Optimization
Date Deposited: 16 Jan 2024 10:13
Last Modified: 27 Mar 2024 09:16
SWORD Depositor: Deep Green
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/16861
PPN: 516540017
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