抄録
The Particle Swarm Optimization (PSO) method is one of the most powerful methods available for solving both unconstrained and constrained global optimization problems. However, knowledge of adaptive strategies for tuning the parameters of the method for application to large-scale nonlinear non-convex optimization problems is as yet limited. This paper describes an adaptive strategy for tuning the parameters of the PSO method based on an analysis of the dynamics of PSO. This adaptive tuning strategy is based on the results of an analysis of the dynamics of average velocity of the particles with successful search processes. The feasibility and advantages of the proposed adaptive PSO method are demonstrated through numerical simulations using a typical global optimization test problem.
