Measuring exploration/exploitation in particle swarms using swarm diversity

An important factor contributing to the success of particle swarm optimization (PSO) is the balance between exploration and exploitation of the swarm. Exploration is typically preferred at the initial stages of the search but is required to gradually give way to exploitation of promising solutions as the search progresses. The diversity of a particle swarm optimization algorithm can be defined, simply, as the degree of dispersion of the particles in the swarm. This dispersion could be defined around some center-point or not. It could also be defined based on the positions of the particles or on their velocities. This paper takes a look at some of the different definitions of swarm diversity with the intention of determining their usefulness in quantifying swarm exploration/exploitation. This work is intended to lay the foundations for the development of a suitable means to quantify the rate of change from exploration to exploitation of a PSO, i.e. the rate of change of diversity.