Adaptive particle swarm optimization algorithm II
Han Li · Kongzhi yu juece · 2009
Adaptive particle swarm optimisation-I(APSO-I)simulates the complex behaviour of social swarm and overlaps the inscrutable decision on the rational behaviour.APSO-Ⅱ is proposed to overcome the poor convergence depth of APSO-Ⅰ.The APSO-Ⅱ algorithm divides the order action(the standard PSO)and the random exploration(the adaptive optimisation)to show the advantage of two optimisation methods.In the stage of adaptive optimisation,the optimal solution is searched in the adjacent space of the best particle.Once the optimal solution is found,the standard PSO will be applied to rapidly explore.Experimental simulations show that APSO-II algorithm is better than DPSO(Dissipation PSO),HPSO(Hierarchical PSO),AEPSO(Adaptive escape PSO),and APSO-I algorithms in the capacity of convergence speed and convergence depth.