Binary String Fitness Characterization and Comparative Partner Selection in Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@Article{Day:2008:TEC,
  title =        "Binary String Fitness Characterization and Comparative
                 Partner Selection in Genetic Programming",
  author =       "Peter Day and Asoke K. Nandi",
  journal =      "IEEE Transactions on Evolutionary Computation",
  year =         "2008",
  month =        dec,
  volume =       "12",
  number =       "6",
  pages =        "724--735",
  keywords =     "genetic algorithms, genetic programming, binary string
                 fitness characterization, comparative partner
                 selection, evolutionary methods, genetic programming
                 benchmarking problems, adaptive crossover and mutation,
                 mate selection, CPS",
  ISSN =         "1089-778X",
  DOI =          "doi:10.1109/TEVC.2008.917201",
  URL =          "http://results.ref.ac.uk/Submissions/Output/832803",
  size =         "12 pages",
  abstract =     "The premise behind all evolutionary methods is
                 survival of the fittest and consequently, individuals
                 require a quantitative fitness measure. This paper
                 proposes a novel strategy for evaluating individual's
                 relative strengths and weaknesses, as well as
                 representing these in the form of a binary string
                 fitness characterization (BSFC); in addition, as
                 customary, an overall fitness value is assigned to each
                 individual. Using the BSFC, we demonstrate both novel
                 population evaluation measures and a pairwise mating
                 strategy, comparative partner selection (CPS), with the
                 aim of evolving a population that promotes effective
                 solutions by reducing population-wide weaknesses. This
                 strategy is tested with six standard genetic
                 programming benchmarking problems.",
  notes =        "Also known as \cite{4472181} 3 bit parity, 5-even
                 parity, 11 mux, quartic, Rastrigin, Sunspot, parsimony
                 pressure, bloat,",
  uk_research_excellence_2014 = "The survival of the fittest
                 characterises evolutionary computational methods,
                 requiring fitness measures for individuals. This paper
                 invents novel strategies for evaluating individual's
                 relative strengths and weaknesses, and representing
                 them in a fundamentally new binary string fitness
                 characterisation (BSFC). A new rigorous paradigm is
                 created by using the BSFC in proposing a pair-wise
                 mating strategy, Comparative Partner Selection, in
                 evolving a population that promotes effective solutions
                 by reducing population-wide weaknesses. Published in a
                 high impact factor journal, this represents a
                 significantly promising development that subsequently
                 led to successes in breast cancer detection,
                 communications (IEEE TWC 2012), and condition
                 monitoring applications.",
}

Genetic Programming entries for Peter Day Asoke K Nandi

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