optiprofiler 1.3.1

Benchmarking optimization solvers

🌐 Website: www.optprof.com

Python

Install OptiProfiler from PyPI:

pip install optiprofiler

You can also install OptiProfiler from conda-forge:

conda install conda-forge::optiprofiler

Note

OptiProfiler includes the S2MPJ problem library by default. Optional problem libraries include PyCUTEst and the SOLAR adapter. PyCUTEst requires a separate installation. SOLAR uses a slim runtime derived from bbopt/solar under LGPL-2.1; see the adapter README and runtime manifest for provenance.

MATLAB

1. Clone the repository using the following command:

git clone https://github.com/optiprofiler/optiprofiler.git

2. In MATLAB, navigate to the folder where the source code is located, and you will see a file named setup.m. Run the following command in the MATLAB command window:

setup

If the optional SOLAR MATLAB adapter is not installed locally, setup asks whether to download it. For non-interactive scripts, pass the choice explicitly:

setup(struct('install_solar', true))
setup(struct('install_solar', false))

When accepted or requested, setup clones optiprofiler/solar_matlab into the local directory matlab/optiprofiler/problem_libs/solar and adds it to the MATLAB path. This directory is a local optional installation, not a submodule of the OptiProfiler repository. Passing install_solar=false skips the prompt and optional download when the adapter is not installed locally, which is useful in CI and batch scripts. The public problem-library name remains solar; use plibs={'solar'} in MATLAB benchmark options.