English, Article edition: THE PARTICLE SWARM AS COLLABORATIVE SAMPLING OF THE SEARCH SPACE JAMES KENNEDY

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Bookmark: http://trove.nla.gov.au/version/134061
Physical Description
  • article
Language
  • English

Edition details

Title
  • THE PARTICLE SWARM AS COLLABORATIVE SAMPLING OF THE SEARCH SPACE
Author
  • JAMES KENNEDY
Physical Description
  • article
Notes
  • The particle swarm algorithm uses principles derived from social psychology to find optimal points in a search space. The present paper decomposes and reinterprets the particle swarm in order to discover new ways of implementing the algorithm. Some essential characteristics of the method are illuminated, and some inessential features are discarded. Various new forms are tested and found to perform well on a suite of test functions. In particular, it is shown that the traditional trajectory formulas can be replaced with random number generators sampling from various symmetrical probability distributions. The excellent performance of these new versions demonstrates that the strength of the algorithm is in the interactions of the particles, rather than in their behavior as individuals.
  • Swarm, social simulation, optimization
  • RePEc:wsi:acsxxx:v:10:y:2007:i:su:p:191-213
Language
  • English
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