For each problem we provide a short description of the problem, notes on the formulation of the problem, and results of computational experiments with general optimization solvers. We currently have results for LANCELOT, MINOS, SNOPT, and LOQO.
Each problem has been implemented in AMPL and (courtesy of GAMS Development Corp.) in GAMS. The report
contains descriptions of the problems, notes on the formulation, graphs of the solutions, and the results of computational experiments. The article
discusses the analysis and interpretation of benchmarking data. The companion Perl script, perf.pl, can be used to create performance profiles for Matlab. The header of the script contains documentation on its use. Michael Friedlander has also written a performance profiling script in Python that uses gnuplot to create encapsulated post-script files.
The current collection (Version 2.0) of COPS problems can be obtained by entering your email address below (so that you can be informed of future software updates) and downloading the compressed tar file that contains the AMPL model and data files or the compressed tar file of GAMS models.
COPS: Keeping optimization software honest.
Alexander Bondarenko
David Bortz
Liz Dolan
Michael Merritt
Jorge Moré