Journal
MATHEMATICAL PROGRAMMING COMPUTATION
Volume 13, Issue 3, Pages 443-490Publisher
SPRINGER HEIDELBERG
DOI: 10.1007/s12532-020-00194-3
Keywords
Mixed integer linear optimization; MIP; Benchmarking; Selection methodology; Instance library
Categories
Funding
- Projekt DEAL
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The sixth version of the MIPLIB, known as MIPLIB 2017, was compiled from an initial pool of 5721 instances, resulting in a collection of 1065 instances with a subset of 240 instances selected for solver performance benchmarking. This selection process utilized a data-driven approach supported by solving a series of mixed integer optimization problems to ensure diversity and balancedness in instance features and performance data.
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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