Abstract
This paper proposes an adaptive particle swarm optimization (PSO) algorithm using the information defined as the average absolute value of velocity of all of the particles, which can be used as an index to understand the briskness of all the particles. While a stability analysis of PSO algorithm is carried out on the basis of not only a simplified model but also simple numerical simulations, an adaptive strategy for tuning one of its parameters is introduced so as to follow a given ideal average velocity by feedback control. The feasibility and advantages of the proposed adaptive PSO algorithm are verified through numerical simulations using some typical global optimization problems. © 2006 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
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