Genetic programming with multiple initial populations generated by simulated annealing

Created by W.Langdon from gp-bibliography.bib Revision:1.4192

  author =       "Takuya Mototsuka and Akira Hara and 
                 Jun-ichi Kushida and Tetsuyuki Takahama",
  title =        "Genetic programming with multiple initial populations
                 generated by simulated annealing",
  booktitle =    "Sixth IEEE International Workshop on Computational
                 Intelligence Applications (IWCIA 2013)",
  year =         "2013",
  month =        "13 " # jul,
  pages =        "113--118",
  keywords =     "genetic algorithms, genetic programming, simulated
                 Annealing Programming, Evolutionary Computation",
  DOI =          "doi:10.1109/IWCIA.2013.6624797",
  ISSN =         "1883-3977",
  abstract =     "Genetic Programming (GP) and Simulated Annealing
                 Programming (SAP) are typical metaheuristic methods for
                 automatic programming. We propose a new method,
                 Parallel - Genetic and Annealing Programming (P-GAP)
                 which combines GP and SAP. In P-GAP, multiple initial
                 populations are generated by SAP. Respective
                 populations evolve by parallel GP. As the generation
                 proceeds, populations are integrated gradually. To
                 examine the effectiveness, we compared P-GAP with the
                 conventional methods in five test problems. As a
                 result, P-GAP showed better performance than GP and
  notes =        "Also known as \cite{6624797}",

Genetic Programming entries for Takuya Mototsuka Akira Hara Jun-ichi Kushida Tetsuyuki Takahama