pyticle

A Python Library for Particle Swarm Intelligence

This package implements the Particle Swarm Optimization (PSO) algorithm in pure python. The only thing you need to is installing the package and call it with the right parameters!

PSO is an interactive meta-heuristic algorithm that uses "particles" as a candidates for solutions. The goal is to move the particles towards the global/local minimum in each iteration.

Installation

Simply install this package by running the following command:

pip install pyticle 

Usage

To minimize the 2D function my_func in range [-15, 10] using 100 particles via 80 iterations:

from pyticle.swarm_optimization import SwarmOptimization
optimizer = SwarmOptimization(cost_func=my_func, particle_num=100, omega_start=1, omega_end=0.0,
 coef=[2.0, 2.0], low_bound=-15.0, high_bound=10,
 boundary_strategy='random', var_size=2, max_iter_num=80, elite_rate=0.1)
optimizer.optimize()

Demo

In this section, you can see the results of using this package for two simple 2D benchmarks. To run the benchmarks, run:

from pyticle.demo_run import demo_run
demo_run()

The Sphere Function

Here is the evolution of 100 particles in 100 iterations to find the minimum of the Sphere function:

Here is the changes in the minimum, average, and maximum values of the cost function of all particles over time:

The Ackley Function

Same as the previous example, this is the evolution of 100 particles in 100 iterations to find the minimum of the Ackley function:

Here is the changes in the minimum, average, and maximum values of the cost function of all particles over time:

Contribution

You are very welcome to contribute to this project with your code (as pull-requests), mention the bugs or ask for new features (as GitHub Issues), or just tell your friends about it!

You can also directly contact me by email.