On the Performance of Particle Swarm Optimizers

Abstract

Since the introduction of the first Particle Swarm Optimization algorithm by James Kennedy and Russell Eberhart in the mid-90’s, many variants of the original algorithm have been proposed. However, there is no general agreement on which variant(s) could be considered the state-of-the-art in the field. This is, in part, due to a general lack of cross-comparisons among variants in the literature. The work reported in this document was carried out with the goal of identifying the best-performing particle swarm optimization algorithms. For practical reasons, we could not compare all the available algorithmic variants. Instead, we focused on those that have been the most widely used variants. We also considered algorithms that incorporate some of the latest developments in field. The comparison of the chosen particle swarm optimization algorithms was based on run-length and solution-quality distributions. These analytical tools allow the comparison of stochastic optimization algorithms in terms of the probabilit