Richards, Mark's Publications (detailed list)

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This page contains the titles and abstracts of papers written by author Richards, Mark, a member of the BYU Neural Networks and Machine Learning (NNML) Research Group. Postscript files are available for most papers. A more concise list is available.

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Choosing a Starting Configuration for Particle Swarm Optimization

  • Authors: Mark Richards and Dan Ventura
  • Abstract: The performance of Particle Swarm Optimization can be improved by strategically selecting the starting positions of the particles. This work suggests the use of generators from centroidal Voronoi tessellations as the starting points for the swarm. The performance of swarms initialized with this method is compared with the standard PSO algorithm on several standard test functions. Results suggest that CVT initialization improves PSO performance in high-dimensional spaces.
  • Reference: Proceedings of the Joint Conference on Neural Networks, pages 2309–2312, July 2004.
  • BibTeX
  • Download the file: pdf

Dynamic Sociometry in Particle Swarm Optimization

  • Authors: Mark Richards and Dan Ventura
  • Abstract: The performance of Particle Swarm Optimization is greatly affected by the size and sociometry of the swarm. This research proposes a dynamic sociometry, which is shown to be more effective on some problems than the standard star and ring sociometries. The performance of various combinations of swarm size and sociometry on six different test functions is qualitatively analyzed.
  • Reference: Proceedings of the Joint Conference on Information Sciences, pages 1557–1560, September 2003.
  • BibTeX
  • Download the file: pdf

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