• DOI:10.1109/TSMCB.2009.2015956
Corpus ID: 11191625

Adaptive Particle Swarm Optimization

@article{Zhan2009AdaptivePS,
  title={Adaptive Particle Swarm Optimization},
  author={Zhi-hui Zhan and Jun Zhang and Y. Li and H. Chung},
  journal={IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)},
  year={2009},
  volume={39},
  pages={1362-1381}
}

Zhi-hui Zhan, Jun Zhang, +1 author H. Chung

Published 2009

Computer Science, Medicine

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…Expand Abstract

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