An analysis of Bare Bones Particle Swarm

Abstract

The bare bones particle swarm (BBPS) is evolved from the canonical particle swarm optimizer (PSO). The velocity term of the canonical PSO is removed in BBPS and replaced by Gaussian sampling strategy. There is no parameter tuning and it is much easier to implement. In the paper, it is proven that the BBPS can be mathematically deduced from the canonical PSO and a more general formula of BBPS is also presented. The results presented in the paper represent initial results of an ongoing research project effort.