<p align="center">
<img width="200" src="https://raw.githubusercontent.com/firefly-cpp/FireflyAlgorithm/master/.github/imgs/firefly_logo.png">
</p>
---
# Firefly Algorithm --- Implementation of Firefly algorithm in Python
---
[](https://pypi.python.org/pypi/fireflyalgorithm)
[](https://pepy.tech/project/fireflyalgorithm)
[](https://aur.archlinux.org/packages/python-fireflyalgorithm)
[](https://github.com/firefly-cpp/FireflyAlgorithm/blob/master/LICENSE)
[](http://isitmaintained.com/project/firefly-cpp/FireflyAlgorithm "Average time to resolve an issue")
[](http://isitmaintained.com/project/firefly-cpp/FireflyAlgorithm "Percentage of issues still open")
[](https://repology.org/project/python:fireflyalgorithm/versions)
[](https://doi.org/10.5281/zenodo.10430919)
## About 📋
This package implements a nature-inspired algorithm for optimization called Firefly Algorithm (FA) in Python programming language. 🌿🔍💻
## Installation 📦
Install FireflyAlgorithm with pip:
```sh
pip install fireflyalgorithm
```
To install FireflyAlgorithm on Fedora, use:
```sh
dnf install python-fireflyalgorithm
```
To install FireflyAlgorithm on Arch Linux, please use an [AUR helper](https://wiki.archlinux.org/title/AUR_helpers):
```sh
$ yay -Syyu python-fireflyalgorithm
```
To install FireflyAlgorithm on Alpine Linux:
```sh
$ apk add py3-fireflyalgorithm
```
## Usage 🚀
```python
from fireflyalgorithm import FireflyAlgorithm
from fireflyalgorithm.problems import sphere
FA = FireflyAlgorithm()
best = FA.run(function=sphere, dim=10, lb=-5, ub=5, max_evals=10000)
print(best)
```
### Test functions 📈
In the `fireflyalgorithm.problems` module, you can find the implementations of 33 popular optimization test problems. Additionally, the module provides a utility function, `get_problem`, that allows you to retrieve a specific optimization problem function by providing its name as a string:
```python
from fireflyalgorithm.problems import get_problem
# same as from fireflyalgorithm.problems import rosenbrock
rosenbrock = get_problem('rosenbrock')
```
For more information about the implemented test functions, [click here](Problems.md).
### Command line interface 🖥️
The package also comes with a simple command line interface which allows you to evaluate the algorithm on several popular test functions. 🔬
```shell
firefly-algorithm -h
```
```text
usage: firefly-algorithm [-h] --problem PROBLEM -d DIMENSION -l LOWER -u UPPER -nfes MAX_EVALS [-r RUNS] [--pop-size POP_SIZE] [--alpha ALPHA] [--beta-min BETA_MIN] [--gamma GAMMA] [--seed SEED]
Evaluate the Firefly Algorithm on one or more test functions
options:
-h, --help show this help message and exit
--problem PROBLEM Test problem to evaluate
-d DIMENSION, --dimension DIMENSION
Dimension of the problem
-l LOWER, --lower LOWER
Lower bounds of the problem
-u UPPER, --upper UPPER
Upper bounds of the problem
-nfes MAX_EVALS, --max-evals MAX_EVALS
Max number of fitness function evaluations
-r RUNS, --runs RUNS Number of runs of the algorithm
--pop-size POP_SIZE Population size
--alpha ALPHA Randomness strength
--beta-min BETA_MIN Attractiveness constant
--gamma GAMMA Absorption coefficient
--seed SEED Seed for the random number generator
```
**Note:** The CLI script can also run as a python module (python -m fireflyalgorithm ...).
## Reference Papers 📚
I. Fister Jr., X.-S. Yang, I. Fister, J. Brest. [Memetic firefly algorithm for combinatorial optimization](http://www.iztok-jr-fister.eu/static/publications/44.pdf) in Bioinspired Optimization Methods and their Applications (BIOMA 2012), B. Filipic and J.Silc, Eds.
Jozef Stefan Institute, Ljubljana, Slovenia, 2012
I. Fister, I. Fister Jr., X.-S. Yang, J. Brest. [A comprehensive review of firefly algorithms](http://www.iztok-jr-fister.eu/static/publications/23.pdf). Swarm and Evolutionary Computation 13 (2013): 34-46.
## License
This package is distributed under the MIT License. This license can be found online at <http://www.opensource.org/licenses/MIT>.
## Disclaimer
This framework is provided as-is, and there are no guarantees that it fits your purposes or that it is bug-free. Use it at your own risk!
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"description": "<p align=\"center\">\n <img width=\"200\" src=\"https://raw.githubusercontent.com/firefly-cpp/FireflyAlgorithm/master/.github/imgs/firefly_logo.png\">\n</p>\n\n---\n\n# Firefly Algorithm --- Implementation of Firefly algorithm in Python\n\n---\n\n[](https://pypi.python.org/pypi/fireflyalgorithm)\n\n\n[](https://pepy.tech/project/fireflyalgorithm)\n[](https://aur.archlinux.org/packages/python-fireflyalgorithm)\n[](https://github.com/firefly-cpp/FireflyAlgorithm/blob/master/LICENSE)\n\n[](http://isitmaintained.com/project/firefly-cpp/FireflyAlgorithm \"Average time to resolve an issue\")\n[](http://isitmaintained.com/project/firefly-cpp/FireflyAlgorithm \"Percentage of issues still open\")\n\n[](https://repology.org/project/python:fireflyalgorithm/versions)\n[](https://doi.org/10.5281/zenodo.10430919)\n\n## About \ud83d\udccb\n\nThis package implements a nature-inspired algorithm for optimization called Firefly Algorithm (FA) in Python programming language. \ud83c\udf3f\ud83d\udd0d\ud83d\udcbb\n\n## Installation \ud83d\udce6\n\nInstall FireflyAlgorithm with pip:\n```sh\npip install fireflyalgorithm\n```\nTo install FireflyAlgorithm on Fedora, use:\n```sh\ndnf install python-fireflyalgorithm\n```\nTo install FireflyAlgorithm on Arch Linux, please use an [AUR helper](https://wiki.archlinux.org/title/AUR_helpers):\n```sh\n$ yay -Syyu python-fireflyalgorithm\n```\nTo install FireflyAlgorithm on Alpine Linux:\n```sh\n$ apk add py3-fireflyalgorithm\n```\n\n## Usage \ud83d\ude80\n\n```python\nfrom fireflyalgorithm import FireflyAlgorithm\nfrom fireflyalgorithm.problems import sphere\n\nFA = FireflyAlgorithm()\nbest = FA.run(function=sphere, dim=10, lb=-5, ub=5, max_evals=10000)\n\nprint(best)\n```\n\n### Test functions \ud83d\udcc8\n\nIn the `fireflyalgorithm.problems` module, you can find the implementations of 33 popular optimization test problems. Additionally, the module provides a utility function, `get_problem`, that allows you to retrieve a specific optimization problem function by providing its name as a string:\n\n```python\nfrom fireflyalgorithm.problems import get_problem\n\n# same as from fireflyalgorithm.problems import rosenbrock\nrosenbrock = get_problem('rosenbrock')\n```\n\nFor more information about the implemented test functions, [click here](Problems.md).\n\n### Command line interface \ud83d\udda5\ufe0f\n\nThe package also comes with a simple command line interface which allows you to evaluate the algorithm on several popular test functions. \ud83d\udd2c\n\n```shell\nfirefly-algorithm -h\n```\n\n```text\nusage: firefly-algorithm [-h] --problem PROBLEM -d DIMENSION -l LOWER -u UPPER -nfes MAX_EVALS [-r RUNS] [--pop-size POP_SIZE] [--alpha ALPHA] [--beta-min BETA_MIN] [--gamma GAMMA] [--seed SEED]\n\nEvaluate the Firefly Algorithm on one or more test functions\n\noptions:\n -h, --help show this help message and exit\n --problem PROBLEM Test problem to evaluate\n -d DIMENSION, --dimension DIMENSION\n Dimension of the problem\n -l LOWER, --lower LOWER\n Lower bounds of the problem\n -u UPPER, --upper UPPER\n Upper bounds of the problem\n -nfes MAX_EVALS, --max-evals MAX_EVALS\n Max number of fitness function evaluations\n -r RUNS, --runs RUNS Number of runs of the algorithm\n --pop-size POP_SIZE Population size\n --alpha ALPHA Randomness strength\n --beta-min BETA_MIN Attractiveness constant\n --gamma GAMMA Absorption coefficient\n --seed SEED Seed for the random number generator\n```\n\n**Note:** The CLI script can also run as a python module (python -m fireflyalgorithm ...).\n\n\n## Reference Papers \ud83d\udcda\n\nI. Fister Jr., X.-S. Yang, I. Fister, J. Brest. [Memetic firefly algorithm for combinatorial optimization](http://www.iztok-jr-fister.eu/static/publications/44.pdf) in Bioinspired Optimization Methods and their Applications (BIOMA 2012), B. Filipic and J.Silc, Eds.\nJozef Stefan Institute, Ljubljana, Slovenia, 2012\n\nI. Fister, I. Fister Jr., X.-S. Yang, J. Brest. [A comprehensive review of firefly algorithms](http://www.iztok-jr-fister.eu/static/publications/23.pdf). Swarm and Evolutionary Computation 13 (2013): 34-46.\n\n## License\n\nThis package is distributed under the MIT License. This license can be found online at <http://www.opensource.org/licenses/MIT>.\n\n## Disclaimer\n\nThis framework is provided as-is, and there are no guarantees that it fits your purposes or that it is bug-free. Use it at your own risk!\n",
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