Simple implementation of Particle Swarm Optimization algorithm written in python3. Particle swarm optimization (PSO) is a computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. It solves a problem by having a population of candidate solutions, here dubbed particles, and moving these particles around in the search-space according to simple mathematical formulae over the particle's position and velocity.
- Install dependencies
pip install numpy- Tweak constants in
pso.py, fitness function, number of iterations etc. - Run
python pso.pyThis project is licensed under the MIT License - see the LICENSE file for details