Particle Swarm Optimization Programming

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@InProceedings{Wu:2010:CASoN,
  author =       "Xiaojun Wu and Ming Zhao and Yaohong Qu",
  title =        "Particle Swarm Optimization Programming",
  booktitle =    "2010 International Conference on Computational Aspects
                 of Social Networks (CASoN)",
  year =         "2010",
  month =        sep,
  pages =        "397--400",
  abstract =     "PSO is a parallel stochastic optimisation algorithm
                 with advantages of less parameters and high efficiency.
                 This paper describes the programming problem in the
                 method of two linear tables with discrete and
                 continuous quantity, then uses discrete PSO algorithm
                 to discrete optimisation and continuous PSO to optimise
                 continuous quantity in the solving process
                 respectively, based on these proposes the Particle
                 Swarm Optimisation Programming algorithm. Finally, GP
                 and PSOP algorithms are compared by applying them to
                 solving programming problem respectively with three
                 typical test functions, the results show that the PSOP
                 algorithm has better convergence precision and
                 stability than the GP algorithm.",
  keywords =     "genetic algorithms, genetic programming, continuous
                 PSO, convergence precision, discrete PSO algorithm,
                 discrete optimization, parallel stochastic optimization
                 algorithm, particle swarm optimization programming,
                 particle swarm optimisation, stochastic programming",
  DOI =          "doi:10.1109/CASoN.2010.96",
  notes =        "sphere, Griewank, Rastrigin. Sch. of Autom.,
                 Northwestern Polytech. Univ., Xi'an, China Also known
                 as \cite{5636594}",
}

Genetic Programming entries for Xiaojun Wu Ming Zhao Yaohong Qu

Citations