Metadata-Version: 2.1
Name: benchmarkfcns
Version: 1.0.0
Summary: A collection of benchmark functions for mathematical optimization algorithms.
Author-Email: Mazhar Ansari Ardeh <mazhar.ansari.ardeh@gmail.com>
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Requires-Python: >=3.7
Provides-Extra: test
Requires-Dist: pytest; extra == "test"
Description-Content-Type: text/markdown
License-File: LICENSE

# BenchmarkFcns
Benchmarkfcns is an effort to provide a public and free implementation of well-known benchmark optimization functions in MATLAB and Python. The repository also contains an implementation of the Artificial Bee Colony algorithm in Python and MATLAB. The implemetation is based on the description of the algorithm in its original paper and is provided as a proof of concept to benchmark the implemented functions.

# How to install
## MATLAB
To install and use this library, it is just required to add the project folders to MATLAB's path. For example, to use the functions in the 'benchmarks/MATLAB' folder, just navigate to this folder with MATLAB's directory explorer or use the command `addpath` with path to the folder on your PC (e.g. `addpath /path/to/benchmarks`).

## Python
To use the functions, please import `benchfunctions.py` from `benchmarks/python` directory. Please note that this package requires the `numpy` library.

# Support
Any bug reports, code contributions, suggestions, feedback and insights are immensely appreciated and will support this project.
