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README.md

This script is an implementation of the Particle Swarm Optimization algorithm in Python. It can be used to perform basic experiments with PSO.

It was written by Nicolas Hoening (http://www.nicolashoening.de) with some inspiration by pseudocode of adaptiveview.com: http://www.adaptiveview.com/articles/ipsop1.html

Actually, this is more than just the algorithm. I added a lot of features to play with. For example:

  • Several topologies (circle, star and geographical neighborhood)
  • Some standard functions to test on (sphere,griewank,rastrigin,rosenbrock)
  • Logging capabilities (to csv format, even code to plot graphs with that in GNU R can be produced)
  • Experiment setups. Average over many iterations and/or automatically change conditions of your choice and let several trials run while you get a fresh cup of coffee :-)

To use it, navigate into the directory where the pypso directory resides, open a Python session and type:

$ import pypso.base $ pypso.base.run()

(you can also navigate into the pypso directory and leave the "pypso."-parts away in the python-session)

There are a lot of things to tweak with in the file conf.py.

If you have comments and/or help, feel free to drop me a line at nhoening [at] gmail [dot] com

-------- GNU Licence ------- This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA'

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An implementation of the Particle Swarm Optimization algorithm in Python, together with some tools for running experimental evaluations.

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