A New Adaptive Particle Swarm Optimization Algorithm
Jinrong Zhu, Jianbao Zhao, Xiaoning Li · 2008
A new adaptive particle swarm optimization algorithm is proposed in this paper. Every particle chooses its inertial factor according to the fitness of itself and the optimal particle in the presented algorithm. Simulation results show that the new algorithm has advantage of global convergence property and can effectively alleviate the problem of premature convergence. At the same time, the experimental results also show that the suggested algorithm is greatly superior to PSO and APSO in terms of robustness.