Particle swarm optimization with an oscillating inertia weight
Kyriakos Kentzoglanakis, Matthew Poole · 2009
In this paper, we propose an alternative strategy of adapting the inertia weight parameter during the course of particle swarm optimization, by means of a non-monotonic inertia weight function of time. Results demonstrate that an oscillating inertia weight function is competitive and in some cases better than established inertia weight functions, in terms of consistency and speed of convergence.