MIPLIB 2017: data-driven compilation of the 6th mixed-integer programming library

We report on the selection process leading to the sixth version of the Mixed Integer Programming Library, MIPLIB 2017. Selected from an initial pool of 5721 instances, the new MIPLIB 2017 collection consists of 1065 instances. A subset of 240 instances was specially selected for benchmarking solver...

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Published in:Mathematical programming computation Vol. 13; no. 3; pp. 443 - 490
Main Authors: Gleixner, Ambros, Hendel, Gregor, Gamrath, Gerald, Achterberg, Tobias, Bastubbe, Michael, Berthold, Timo, Christophel, Philipp, Jarck, Kati, Koch, Thorsten, Linderoth, Jeff, Lübbecke, Marco, Mittelmann, Hans D., Ozyurt, Derya, Ralphs, Ted K., Salvagnin, Domenico, Shinano, Yuji
Format: Journal Article
Language:English
Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2021
Springer Nature B.V
Subjects:
Full Length Paper
Integer programming
Libraries
Mathematics
Mathematics and Statistics
Mathematics of Computing
Mixed integer
Operations Research/Decision Theory
Optimization
Theory of Computation
90C10
Mixed integer linear optimization
MIP
90C11
90C06
Benchmarking
Instance library
Selection methodology
90C09
ISSN:1867-2949, 1867-2957
Online Access:Get full text
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Summary:We report on the selection process leading to the sixth version of the Mixed Integer Programming Library, MIPLIB 2017. Selected from an initial pool of 5721 instances, the new MIPLIB 2017 collection consists of 1065 instances. A subset of 240 instances was specially selected for benchmarking solver performance. For the first time, these sets were compiled using a data-driven selection process supported by the solution of a sequence of mixed integer optimization problems, which encode requirements on diversity and balancedness with respect to instance features and performance data.
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ISSN:1867-2949
1867-2957
DOI:10.1007/s12532-020-00194-3