PSOGP: A Genetic Programming Based Adaptable Evolutionary Hybrid Particle Swarm Optimization

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@Article{Rashid:2010:IJICIC,
  author =       "Muhammad Rashid and A. {Rauf Baig}",
  title =        "PSOGP: A Genetic Programming Based Adaptable
                 Evolutionary Hybrid Particle Swarm Optimization",
  journal =      "International Journal of Innovative Computing,
                 Information and Control",
  year =         "2010",
  volume =       "6",
  number =       "1",
  pages =        "287--296",
  month =        jan,
  email =        "rashid.nuces@gmail.com",
  keywords =     "genetic algorithms, genetic programming, particle
                 swarm optimisation, function optimisation, evolution,
                 velocity update equation",
  ISSN =         "1349-4198",
  URL =          "http://www.ijicic.org/icic08-si01-13-1.pdf",
  abstract =     "In this study we describe a method for extending
                 particle swarm optimization. We have presented a novel
                 approach for avoiding premature convergence to local
                 minima by the introduction of diversity in the swarm.
                 The swarm is made more diverse and is encouraged to
                 explore by employing a mechanism which allows each
                 particle to use a different equation to update its
                 velocity. This equation is also continuously evolved
                 through the use of genetic programming to ensure
                 adaptability. We compare two variations of our
                 algorithm, one using random initialisation while in the
                 second one we use partial non-random initalization
                 which forces some particles to use the standard PSO
                 velocity update equation. Results from experimentation
                 suggest that the modified PSO with complete random
                 initialisation shows promise and has potential for
                 improvement. It is particularly very good at finding
                 the exact optimum.",
  notes =        "http://www.ijicic.org/",
}

Genetic Programming entries for Muhammad Rashid Abdul Rauf Baig

Citations