OPFUNU (OPtimization benchmark FUnctions in NUmpy) is the largest python library for cutting-edge numerical
optimization benchmark functions. Contains all CEC competition functions from 2005, 2008, 2010, 2013, 2014, 2015,
2017, 2019, 2020, 2021, 2022. Besides, more than 300 traditional functions with different dimensions are implemented.
- Free software: GNU General Public License (GPL) V3 license
- Total problems: > 500 problems
- Documentation: https://opfunu.readthedocs.io
- Python versions: >= 3.7.x
- Dependencies: numpy, matplotlib
Installation and Usage
Install with pip
Install the current PyPI release:
$ pip install opfunu
After installation, you can import and check version of Opfunu:
$ python
>>> import opfunu
>>> opfunu.__version__
>>> dir(opfunu)
>>> help(opfunu)
>>> opfunu.FUNC_DATABASE
>>> opfunu.CEC_DATABASE
>>> opfunu.ALL_DATABASE
>>> opfunu.get_functions_by_classname("CEC2014")
>>> opfunu.get_functions_based_classname("2015")
>>> opfunu.get_functions_by_ndim(30)
>>> opfunu.get_functions_based_ndim(2)
>>> opfunu.get_all_named_functions()
>>> opfunu.get_all_cec_functions()
>>> opfunu.get_functions()
>>> opfunu.get_cecs()
Lib's structure
docs
examples
opfunu
cec_based
cec.py
cec2005.py
cec2008.py
...
cec2021.py
cec2022.py
name_based
a_func.py
b_func.py
...
y_func.py
z_func.py
utils
operator.py
validator.py
visualize.py
__init__.py
benchmark.py
README.md
setup.py
Let's go through some examples.
Examples
How to get the function and use it
1st way
from opfunu.cec_based.cec2014 import F12014
func = F12014(ndim=30)
func.evaluate(func.create_solution())
from opfunu.cec_based import F102014
func = F102014(ndim=50)
func.evaluate(func.create_solution())
2nd way
import opfunu
funcs = opfunu.get_functions_by_classname("F12014")
func = funcs[0](ndim=10)
func.evaluate(func.create_solution())
all_funcs_2014 = opfunu.get_functions_based_classname("2014")
print(all_funcs_2014)
For more usage examples please look at examples folder.
Get helps (questions, problems)
Cite Us
If you are using opfunu in your project, we would appreciate citations:
@software{thieu_nguyen_2020_3711682,
author = {Nguyen Van Thieu},
title = {Opfunu: An Open-source Python Library for Optimization Benchmark Functions},
year = 2020,
publisher = {Zenodo},
doi = {10.5281/zenodo.3620960},
url = {https://doi.org/10.5281/zenodo.3620960.}
}
References
1. http://benchmarkfcns.xyz/fcns
2. https://en.wikipedia.org/wiki/Test_functions_for_optimization
3. https://www.cs.unm.edu/~neal.holts/dga/benchmarkFunction/
4. http://www.sfu.ca/~ssurjano/optimization.html
5. A Literature Survey of Benchmark Functions For Global Optimization Problems (2013)
6. Problem Definitions and Evaluation Criteria for the CEC 2014 Special Session and Competition on Single Objective Real-Parameter Numerical Optimization