Adaptive Particle Swarm Optimization

@article{Zhan2009AdaptivePS,
  title={Adaptive Particle Swarm Optimization},
  author={Zhi-hui Zhan and Jun Zhang and Yun Li and Henry Shu-hung Chung},
  journal={IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)},
  year={2009},
  volume={39},
  pages={1362-1381}
}
  • Zhi-hui Zhan, Jun Zhang, H. Chung
  • Published 1 December 2009
  • Computer Science
  • IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)
An adaptive particle swarm optimization (APSO) that features better search efficiency than classical particle swarm optimization (PSO) is presented. [] Key Method The APSO consists of two main steps. First, by evaluating the population distribution and particle fitness, a real-time evolutionary state estimation procedure is performed to identify one of the following four defined evolutionary states, including exploration, exploitation, convergence, and jumping out in each generation. It enables the automatic…

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