A Python package for general minimization, where derivatives are not available, using random subspaces. For a description of this algorithm, see this paper.
For lower-dimensional problems, consider using the more actively maintained Py-BOBYQA.
Citation
If you use RSDFO-Q in an academic work, please cite the following paper:
C. Cartis and L. Roberts, Randomized Subspace Derivative-Free Optimization with Quadratic Models and Second-Order Convergence. Optimization Methods and Software, to appear.
A preprint version of this paper can be found on arXiv.
Installation
You can install RSDFO-Q by cloning this repository and installing with pip:
$ git clone https://github.com/lindonroberts/rsdfoq.git
$ cd rsdfoq
$ ls <-- check for pyproject.toml
$ pip install -e .RSDFO-Q requires NumPy, SciPy and pandas, but these will be installed automatically if they are not already available.
Usage
Examples for how to use RSDFO-Q may be found in the examples directory.
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