On this page, we maintain a collection of black-box optimization problems that we routinely use to develop BAM. Some problems come from real-world applications, while others are synthetic and help test, develop, or challenge black-box optimization solvers:
- rs13: This collection includes 502 continuous nonlinear problems from [1], with up to 300 variables. For these problems, we provide:
- Python files for calling BAM through its Sci-Py style Python interface or full-control Python class
- Simulation executables for Linux AMD/Intel, Linux ARM64, Windows, OSX Intel, and OSX M Series, which can be used when calling BAM from the command line
- Fortran source codes for generating executables locally
- ps22: This collection includes 267 mixed-integer nonlinear problems from [2], with up to 470 variables. For these problems, we provide:
- Python files for calling BAM through its Sci-Py style Python interface or full-control Python class
- Simulation executables for Linux AMD/Intel, Linux ARM64, Windows, macOS Intel, and macOS M Series, which can be used when calling BAM from the command line
- Fortran source codes for generating executables locally
Sources:
- Rios, L. M. and N. V. Sahinidis, Derivative-free optimization: A review of algorithms and comparison of software implementations, Journal of Global Optimization, 56, 1247-1293, 2013.
- Ploskas, N. and N. V. Sahinidis, Review and comparison of algorithms and software for mixed-integer derivative-free optimization, Journal of Global Optimization, 82, 433-462, 2022.