Binary String Fitness Characterization and Comparative Partner Selection in Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@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",
• volume = "12",
• number = "6",
• pages = "724--735",
• month = dec,
• 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

Citations