Adaptive particle swarm optimization algorithm

The particle swarm optimization (PSO) has exhibited good performance on optimization. However, the parameters, which greatly influence the algorithm stability and performance, are selected depending on experience of designer. The selection of parameters needs to consider both the convergence and avoiding premature convergence. Adaptive PSO (APSO) was presented, based on the stability criterion of the PSO as a time-varying discrete system. Simulation results of some well-known problems show that APSO not only ensure the stability of algorithm, but also avoid premature convergence effectively and clearly outperform the standard PSO.