Degeneracy Reduction or Duplicate Elimination? An Analysis on the Performance of Attributed Grammatical Evolution with Lookahead to Solve the Multiple Knapsack Problem

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{Karim:2011:NICSO,
  author =       "Muhammad Karim and Conor Ryan",
  title =        "Degeneracy Reduction or Duplicate Elimination? An
                 Analysis on the Performance of Attributed Grammatical
                 Evolution with Lookahead to Solve the Multiple Knapsack
                 Problem",
  booktitle =    "Nature Inspired Cooperative Strategies for
                 Optimization (NICSO 2011)",
  year =         "2012",
  editor =       "David Pelta and Natalio Krasnogor and 
                 Dan Dumitrescu and Camelia Chira and Rodica Lung",
  volume =       "387",
  series =       "Studies in Computational Intelligence",
  chapter =      "18",
  pages =        "247--266",
  address =      "Cluj-Napoca, Romania",
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming, grammatical
                 evolution, attribute grammar",
  isbn13 =       "978-3-642-24093-5",
  DOI =          "doi:10.1007/978-3-642-24094-2_18",
  abstract =     "This paper analyses the impact of having degenerate
                 code and duplicate elimination in an attribute grammar
                 with look ahead (AG+LA) approach, a recently proposed
                 mapping process for Grammatical Evolution (GE) using
                 attribute grammar (AG) with a lookahead feature to
                 solve heavily constrained multiple knapsack problems
                 (MKP). Degenerate code, as used in DNA, is code in
                 which different codons can represent the same thing.
                 Many developmental systems, such as (GE), use a
                 degenerate encoding to help promote neutral mutations,
                 that is, minor genetic changes that do not result in a
                 phenotypic change. Early work on GE suggested that at
                 least some level of degeneracy has a significant impact
                 on the quality of search when compared to the system
                 with none. Duplicate elimination techniques, as opposed
                 to degenerate encoding, are employed in decoder-based
                 Evolutionary Algorithms (EAs) to ensure that the newly
                 generated solutions are not already contained in the
                 current population. The results and analysis show that
                 it is crucial to incorporate duplicate elimination to
                 improve the performance of AG+LA. Reducing level of
                 degeneracy is also important to improve search
                 performance, specially for the large instances of the
                 MKP.",
  affiliation =  "University of Limerick, Ireland",
}

Genetic Programming entries for Muhammad Rezaul Karim Conor Ryan

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