Grammatical Evolution of Local Search Heuristics

Created by W.Langdon from gp-bibliography.bib Revision:1.2031

@Article{Burke:2011:ieeeTEC,
  author =       "Edmund K. Burke and Matthew R. Hyde and 
                 Graham Kendall",
  title =        "Grammatical Evolution of Local Search Heuristics",
  journal =      "IEEE Transactions on Evolutionary Computation",
  note =         "Accepted for future publication",
  keywords =     "genetic algorithms, genetic programming, Grammatical
                 Evolution, Grammar, Heuristic algorithms, Production,
                 Search problems, Bin packing, heuristics, local search,
                 stock cutting",
  ISSN =         "1089-778X",
  doi =          "doi:10.1109/TEVC.2011.2160401",
  size =         "12 pages",
  abstract =     "Genetic programming approaches have been employed in
                 the literature to automatically design constructive
                 heuristics for cutting and packing problems. These
                 heuristics obtain results superior to human-created
                 constructive heuristics, but they do not generally
                 obtain results of the same quality as local search
                 heuristics, which start from an initial solution and
                 iteratively improve it. If local search heuristics can
                 be successfully designed through evolution, in addition
                 to a constructive heuristic which initialises the
                 solution, then the quality of results which can be
                 obtained by automatically generated algorithms can be
                 significantly improved. This paper presents a
                 grammatical evolution methodology which automatically
                 designs good quality local search heuristics that
                 maintain their performance on new problem instances.",
  notes =        "iGE also known as \cite{6029980}",
}

Genetic Programming entries for Edmund Burke Matthew R Hyde Graham Kendall