Comparison of Parallel Linear Genetic Programming Implementations

Created by W.Langdon from gp-bibliography.bib Revision:1.4549

  author =       "David Grochol and Lukas Sekanina",
  title =        "Comparison of Parallel Linear Genetic Programming
  booktitle =    "Proceedings of the 22nd International Conference on
                 Soft Computing (MENDEL 2016)",
  year =         "2016",
  editor =       "Radek Matousek",
  volume =       "576",
  series =       "AISC",
  pages =        "64--76",
  address =      "Brno, Czech Republic",
  month =        jun # " 8-10",
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming, parallel GP",
  isbn13 =       "978-3-319-58087-6",
  ISSN =         "2194-5357",
  DOI =          "doi:10.1007/978-3-319-58088-3_7",
  abstract =     "Linear genetic programming (LGP) represents candidate
                 programs as sequences of instructions for a register
                 machine. In order to accelerate the evaluation time of
                 candidate programs and reduce the overall time of
                 evolution, we propose various parallel implementations
                 of LGP suitable for the current multi-core processors.
                 The implementations are based on a parallel evaluation
                 of candidate programs and the island model of the
                 parallel evolutionary algorithm in which the
                 subpopulations are evolved independently, but some
                 genetic material can be exchanged by means of the
                 migration. Proposed implementations are evaluated using
                 three symbolic regression problems and a hash function
                 design problem.",
  notes =        "
                 ICSC-MENDEL 2016 Recent Advances in Soft Computing",

Genetic Programming entries for David Grochol Lukas Sekanina