Evolution of Force-Generating Equations for PSO using GP

We extend our previous research on evolving the physical forces which control particle swarms by considering additional ingredients, such as the velocity of the neighbourhood best and time, and different neighbourhood topologies, namely the global and local ones. We test the evolved extended PSOs (XPSOs) on various classes of benchmark problems. We show that evolutionary computation, and in particular genetic programming (GP), can automatically generate new PSO algorithms that outperform standard PSOs designed by people as well as some previously evolved ones.