An Improved GAPSO Hybrid Programming Algorithm

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@InProceedings{Wu:2009:ICIECS,
  author =       "Xiaojun Wu and Ying Wang and Tiantian Zhang",
  title =        "An Improved GAPSO Hybrid Programming Algorithm",
  booktitle =    "International Conference on Information Engineering
                 and Computer Science, ICIECS 2009",
  year =         "2009",
  month =        dec,
  abstract =     "GAPSO hybrid programming algorithm, which is a
                 concise, effective and stable algorithm to solve the
                 hierarchical problem based on GP algorithm. In terms of
                 the specific characteristics of discrete magnitude and
                 continuous magnitude, as well as the superiority of PSO
                 in continuous quantity optimisation, in this paper we
                 propose an improved algorithm, which optimises
                 continuous magnitude by PSO while using GP for discrete
                 magnitude optimization. Then through mass contrast
                 experiments with GAPSO hybrid programming algorithm, we
                 could see that Improved GAPSO hybrid programming
                 algorithm is more stable and effective in function
                 modelling.",
  keywords =     "genetic algorithms, genetic programming, GP algorithm,
                 continuous magnitude, continuous quantity optimisation,
                 discrete magnitude, function modelling, hierarchical
                 problem, improved GAPSO hybrid programming, mass
                 contrast experiments, mathematical programming,
                 particle swarm optimisation",
  DOI =          "doi:10.1109/ICIECS.2009.5365983",
  notes =        "Sch. of Autom., Northwestern Polytech. Univ., Xi'an,
                 China. Also known as \cite{5365983}",
}

Genetic Programming entries for Xiaojun Wu Ying Wang Tiantian Zhang

Citations