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Genetic Algorithm Particle Swarm Optimization Implemented in Python

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Particle Swarm Optimization (PSO)

This project show how to implement the Particle Swarm Optimization (PSO) to minimize/maximize some function. All codes are writen in Python 3.x and Jupyter Notebook. Most part of the code are implemented in Jupyter Notebook. The notebook explains the PSO method by one brief description given by Wikipedia. Also, in the notebook, it's implemented the pseudo-code and we running one example in a specific function.

Getting Started

All you need for running this project is Python 3.x and Jupyter Notebook. It's also necessary to have the NumPy library installed in your Python 3.x distribution.

Prerequisites

Installing Python3.x:

apt-get install python3.x

Installing Jupyter Notebook with pip:

python3.x -m pip install --upgrade pip
python3.x -m pip install jupyter

Installing the NumPy library with pip:

python3.x -m pip install numpy

Jupyter Notebooks

Genetic Algorithm - Particle Swarm Optimization - Notebook with the description and execution of the PSO method to maximize one specifc function.

Authors

See also the list of contributors who participated in this project.

License

This project is licensed under the MIT License - see the LICENSE.md file for details

Acknowledgments

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Genetic Algorithm Particle Swarm Optimization Implemented in Python

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