A hybrid gene expression programming algorithm based on orthogonal design

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@Article{journals/ijcisys/0009M16,
  title =        "A hybrid gene expression programming algorithm based
                 on orthogonal design",
  author =       "Jie Yang and Jun Ma",
  journal =      "Int. J. Computational Intelligence Systems",
  year =         "2016",
  volume =       "9",
  number =       "4",
  pages =        "778--787",
  keywords =     "genetic algorithms, genetic programming, gene
                 expression programming, evolutionary computation,
                 orthogonal design, evolutionary stable strategy",
  ISSN =         "1875-6883",
  bibdate =      "2017-05-18",
  bibsource =    "DBLP,
                 http://dblp.uni-trier.de/db/journals/ijcisys/ijcisys9.html#0009M16",
  URL =          "http://www.atlantis-press.com/php/download_paper.php?id=25868727",
  DOI =          "doi:10.1080/18756891.2016.1204124",
  abstract =     "The last decade has witnessed a great interest on the
                 application of evolutionary algorithms, such as genetic
                 algorithm (GA), particle swarm optimisation (PSO) and
                 gene expression programming (GEP), for optimisation
                 problems. This paper presents a hybrid algorithm by
                 combining the GEP algorithm and the orthogonal design
                 method. A multiple-parent crossover operator is
                 introduced for the chromosome reproduction using the
                 orthogonal design method. In addition, an evolutionary
                 stable strategy is also employed to maintain the
                 population diversity during the evolution. The
                 efficiency of the proposed algorithm is evaluated using
                 three benchmark problems. The results demonstrate that
                 the proposed hybrid algorithm has a better
                 generalisation ability compared to conventional
                 algorithms.",
}

Genetic Programming entries for Jie Yang Jun Ma

Citations