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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Vydané v:Mathematical programming computation Ročník 13; číslo 3; s. 443 - 490
Hlavní autori: 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
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2021
Springer Nature B.V
Predmet:
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
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Shrnutí: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.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
ISSN:1867-2949
1867-2957
DOI:10.1007/s12532-020-00194-3