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GasLib—A Library of Gas Network Instances

Discrete Optimization, Friedrich-Alexander-Universität Erlangen-Nürnberg, Cauerstr. 11, 91058 Erlangen, Germany
Energie Campus Nürnberg, Fürther Str. 250, 90429 Nürnberg, Germany
Zuse Institut Berlin, Takustr. 7, 14195 Berlin, Germany
Institut für Mathematische Optimierung, Technische Universität Braunschweig, Universitätsplatz 2, 38106 Braunschweig, Germany
School of Electrical and Computer Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
Institut für Angewandte Mathematik, Leibniz Universität Hannover, Welfengarten 1, 30167 Hannover, Germany
Department of Mathematics, Technische Universität Darmstadt, Dolivostr. 15, 64293 Darmstadt, Germany
Author to whom correspondence should be addressed.
Received: 6 November 2017 / Revised: 18 November 2017 / Accepted: 23 November 2017 / Published: 1 December 2017
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. View Full-Text
Keywords: gas transport; networks; problem instances; mixed-integer nonlinear optimization; GasLib gas transport; networks; problem instances; mixed-integer nonlinear optimization; GasLib
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MDPI and ACS Style

Schmidt, M.; Aßmann, D.; Burlacu, R.; Humpola, J.; Joormann, I.; Kanelakis, N.; Koch, T.; Oucherif, D.; Pfetsch, M.E.; Schewe, L.; Schwarz, R.; Sirvent, M. GasLib—A Library of Gas Network Instances. Data 2017, 2, 40.

AMA Style

Schmidt M, Aßmann D, Burlacu R, Humpola J, Joormann I, Kanelakis N, Koch T, Oucherif D, Pfetsch ME, Schewe L, Schwarz R, Sirvent M. GasLib—A Library of Gas Network Instances. Data. 2017; 2(4):40.

Chicago/Turabian Style

Schmidt, Martin, Denis Aßmann, Robert Burlacu, Jesco Humpola, Imke Joormann, Nikolaos Kanelakis, Thorsten Koch, Djamal Oucherif, Marc E. Pfetsch, Lars Schewe, Robert Schwarz, and Mathias Sirvent. 2017. "GasLib—A Library of Gas Network Instances" Data 2, no. 4: 40.

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