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MIPLIB 2017: Data-Driven Compilation of the 6th Mixed-Integer Programming Library

Ambros Gleixner (gleixner***at***zib.de)
Gregor Hendel (hendel***at***zib.de)
Gerald Gamrath (gamrath***at***zib.de)
Tobias Achterberg (achterberg***at***gurobi.com)
Michael Bastubbe (bastubbe***at***or.rwth-aachen.de)
Timo Berthold (timoberthold***at***fico.com)
Philipp M. Christophel (philipp.christophel***at***sas.com)
Kati Jarck (kati.jarck***at***mosek.com)
Thorsten Koch (koch***at***zib.de)
Jeff Linderoth (linderoth***at***wsc.edu)
Marco Lübbecke (luebbecke***at***or.rwth-aachen.de)
Hans D. Mittelmann (mittelmann***at***asu.edu)
Derya Ozyurt (dozyurt***at***mathworks.com)
Ted K. Ralphs (ted***at***lehigh.edu)
Domenico Salvagnin (domenico.salvagnin***at***unipd.it)
Yuji Shinano (shinano***at***zib.de)

Abstract: We report on the selection process leading to the sixth version of the Mixed Integer Programming Library. Selected from an initial pool of 5,721 instances, the new MIPLIB 2017 collection consists of 1,065 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.

Keywords: MIP; instance library; benchmarking; selection methodology

Category 1: Integer Programming ((Mixed) Integer Linear Programming )

Category 2: Optimization Software and Modeling Systems (Optimization Software Benchmark )


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Entry Submitted: 07/12/2019
Entry Accepted: 07/12/2019
Entry Last Modified: 06/12/2020

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