Swarm Intelligence with Particle Swarm Optimization

Project Description

This project implements a Particle Swarm Optimization (PSO) algorithm for swarm intelligence research. It includes a map space to represent the search space, and utilities for plotting and data handling.

Getting Started

These instructions will get you a copy of the project up and running on your local machine.

Prerequisites

• MATLAB (version 2023a or newer)
• Libraries:
  • [yaml] (https://github.com/MartinKoch123/yaml) by Martin Koch
  • [Text progress bar (CLI & GUI)] (https://www.mathworks.com/matlabcentral/fileexchange/66270-text-progress-bar-cli-gui) by Girmi Schouten
  • [Beautiful and distinguishable line colors + colormap] (https://www.mathworks.com/matlabcentral/fileexchange/42673-beautiful-and-distinguishable-line-colors-colormap) by Jonathan C. Lansey
  • [TSPSEARCH] (https://www.mathworks.com/matlabcentral/fileexchange/71226-tspsearch) by Jonas Lundgren

Installing

A step-by-step series of examples that tell you how to get a development environment running.

1. Clone the repo: git clone https://github.com/austinturbs/PSO-UUV
2. Open MATLAB and set the project directory as PSO-UUV
3. Ensure the pre-requisite libaries are a part of the MATLAB path.
4. Select/edit parameters in user-configurable file - see [config.yaml] (config.yaml) for details.
5. Run SwarmDriver.m with the path to a configuration file as the input argument.

Authors

• Austin Turbeville (austinturbs)

License

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

Acknowledgments

• Thesis Advisor:
  • Dr. Neil Palumbo
• Thesis Readers:
  • Dr. Cleon Davis
  • Dr. John Samsundar