Dynamic-probabilistic particle swarms

  • Authors:
  • James Kennedy

  • Affiliations:
  • US Bureau of Labor Statistics, Washington DC

  • Venue:
  • GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
  • Year:
  • 2005

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Abstract

The particle swarm algorithm is usually a dynamic process, where a point in the search space to be tested depends on the previous point and the direction of movement. The process can be decomposed, and probability distributions around a center can be used instead of the usual trajectory approach. A version that is both dynamic and Gaussian looks very promising.