Abstract:

According to the search failure for large-scale problem via the particle swarm optimization algorithm, the convergence of particle swarm optimization algorithm is analyzed and the relationship between the particle velocity and the search failure is pointed out. Then, an adaptive parameter-adjusting particle swarm optimization algorithm according to the velocity information is put forward. Under the convergent conditions, the proposed algorithm can perform the search by adaptively adjusting the parameters according to the ideal velocity. Experimental results indicate that the proposed algorithm avoids the local optimization and divergence commonly occurred in the conventional particle swarm optimization algorithm in multi-dimension and multi-peak conditions.

Key words: particle swarm optimization algorithm, adaptability, average velocity