Journal of Artificial Evolution and Applications
Volume 2008 (2008), Article ID 761459, 10 pages
doi:10.1155/2008/761459
Research Article
Dynamics and Stability of the Sampling Distribution of Particle Swarm Optimisers via Moment Analysis
Department of Computing and Electronic Systems, University of Essex, Wivenhoe Park, Colchester CO4 3SQ, UK
Received 23 July 2007; Accepted 3 December 2007
Academic Editor: T. Blackwell
Copyright © 2008 Riccardo Poli. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
For stochastic optimisation algorithms, knowing the probability distribution with which
an algorithm allocates new samples in the search space is very important, since this explains
how the algorithm really works and is a prerequisite to being able to match algorithms to
problems. This is the only way to beat the limitations highlighted by the no-free lunch theory.
Yet, the sampling distribution for velocity-based particle swarm optimisers has remained a
mystery for the whole of the first decade of PSO research. In this paper, a method is presented
that allows one to exactly determine all the characteristics of a PSO's sampling distribution
and explain how it changes over time during stagnation (i.e., while particles are in search for
a better personal best) for a large class of PSO's.