Heterogeneous particle swarm optimizers

  title={Heterogeneous particle swarm optimizers},
  author={Marco Antonio Montes de Oca and Jorge Pe{\~n}a and Thomas St{\"u}tzle and Carlo Pinciroli and Marco Dorigo},
  journal={2009 IEEE Congress on Evolutionary Computation},
Particle swarm optimization (PSO) is a swarm intelligence technique originally inspired by models of flocking and of social influence that assumed homogeneous individuals. During its evolution to become a practical optimization tool, some heterogeneous variants have been proposed. However, heterogeneity in PSO algorithms has never been explicitly studied and some of its potential effects have therefore been overlooked. In this paper, we identify some of the most relevant types of heterogeneity… CONTINUE READING
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Montes de Oca and Thomas Stützle . Convergence behavior of the fully informed particle swarm optimization algorithm

  • M. Keijzer
  • Proceedings of the Genetic and Evolutionary…
  • 2008

Built by Animals

  • M. Hansell
  • 2007
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