Comparison of mixed-integer derivative-free optimization algorithms

This page accompanies the paper by Nikolaos Ploskas and Nikolaos V. Sahinidis: Review and comparison of algorithms and software for mixed-integer derivative-free optimization, Journal of Global Optimization, 2021. The paper presents results from the solution of 267 test problems with 13 solvers. Here, we provide all test problems and detailed results that can be used to (a) reproduce the results of the paper and (b) facilitate comparisons with other derivative-free optimization algorithms.

Models in GAMS format:
All
pure integer || binary || non binary || mixed-integer
one to ten variables || eleven to fifty variables || over fifty variables

Models in C format:
The models are available in C source code.

problemdata files for models: problemdata.zip
Results for all solvers are included in the following file: midfo_results.zip
Information about the format of the result files is given in the following README

Results for individual solvers:
BFO || DAKOTA/MADS || DAKOTA/SOGA || DFLBOX || DFLGEN|| MIDACO || MISO || NOMAD || SNOBFIT || TOMLAB/GLCDIRECT || TOMLAB/GLCFAST || TOMLAB/GLCSOLVE || TOMLAB/MSNLP

For the convenience of further testing with the above problems, we provide a complete listing of test problems and model statistics.