https://github.com/firefly-cpp/fireflyalgorithm

Implementation of Firefly Algorithm in Python
https://github.com/firefly-cpp/fireflyalgorithm

firefly-algorithm optimization optimization-algorithms swarm-intelligence

Last synced: 3 months ago
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Implementation of Firefly Algorithm in Python

Host: GitHub
URL: https://github.com/firefly-cpp/fireflyalgorithm
Owner: firefly-cpp
License: mit
Created: 2017-01-02T10:43:04.000Z (over 8 years ago)
Default Branch: master
Last Pushed: 2025-01-04T20:03:28.000Z (6 months ago)
Last Synced: 2025-03-29T00:12:47.140Z (3 months ago)
Topics: firefly-algorithm, optimization, optimization-algorithms, swarm-intelligence
Language: Python
Homepage:
Size: 310 KB
Stars: 59
Watchers: 3
Forks: 28
Open Issues: 0
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
- Citation: CITATION.cff

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README

        


  





Firefly Algorithm --- Implementation of Firefly algorithm in Python





  

  

  

  

  

    

  





  

  

  

  

  





  





  📋 About •

  📦 Installation •

  🚀 Usage •

  📚 Reference Papers •

  📄 Cite us •

  🔑 License



## 📋 About

This package implements a nature-inspired algorithm for optimization called Firefly Algorithm (FA) in Python programming language. 🌿🔍💻

## 📦 Installation

To install FireflyAlgorithm with pip, use:

```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, use:

```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, D. Fister. [A Brief Review of Nature-Inspired Algorithms for Optimization](http://www.iztok-jr-fister.eu/static/publications/21.pdf). Elektrotehniški vestnik, 80(3), 116-122, 2013.

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.

## 📄 Cite us

Fister Jr., I., Pečnik, L., & Stupan, Ž. (2023). firefly-cpp/FireflyAlgorithm: 0.4.3 (0.4.3). Zenodo. [https://doi.org/10.5281/zenodo.10430919](https://doi.org/10.5281/zenodo.10430919)

## 🔑 License

This package is distributed under the MIT License. This license can be found online at .

## 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!