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

By Ambros M. Gleixner, Gregor Hendel, Gerald Gamrath, Tobias Achterberg, Michael Bastubbe, Timo Berthold, Philipp M. Christophel, Kati Jarck, Thorsten Koch, Jeff T. Linderoth and 6 more. Mathematical Programming Computation, 2021

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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.

Subfields: Computational Theory and Mathematics, Management Science and Operations Research, Numerical Analysis

View Paper: https://www.semanticscholar.org/paper/69cb96de02da818d6336616c23fe934fb3562194

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