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Keywords:

  • global optimization;
  • swarm intelligence;
  • particle swarm optimization;
  • adaptive parameter tuning

Abstract

This paper presents a self-adjusting strategy for tuning the parameters of particle swarm optimization (PSO) based on some numerical analysis of the behavior of PSO. The proposed adaptive tuning strategy is based on self-tuning of the parameters of PSO, a strategy that utilizes the information about the frequency of an updated group best of a swarm. The feasibility and advantages of the proposed self-adjusting PSO (SAPSO) algorithm are demonstrated through some numerical simulations using four benchmark problems. Copyright © 2010 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.