PySwallow

PySwallow is a library of Particle Swarm Optimisation algorithms implemented in Python.

Particle Swarm Optimisation is a stochastic population-based optimisation technique developed by Kennedy and Eberhart in 1995. Mathematically, swarming is the collective decentralised motion of a large number of self-propelled entities as a collective animal behaviour and is exhibited by many living creatures - including birds, i.e. swallows.

A swarm of particles represent a group of potential solutions moving in n-dimensional space, each particle has an associated position and velocity. Particle Swarm Optimisation aims to minimise any given objective function through manouvering these particles such that a global-optimum position/solution is found.

Development Goals

The aim of PySwallow is to develop an extensible research toolkit for Particle Swarm Optimisation - providing researchers/students with the resources required to implement the algorithms in their own work.