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Issue:Generalized net for evaluation of the genetic algorithm fitness function

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Title of paper: Generalized net for evaluation of the genetic algorithm fitness fuction
Author(s):
Olympia Roeva
Centre for Biomedical Engineering — Bulgarian Academy of Sciences, Acad. G. Bonchev Str., Bl. 105, Sofia-1113, BULGARIA
olympia@clbme.bas.bg
Krassimir Atanassov
Centre for Biomedical Engineering — Bulgarian Academy of Sciences, Acad. G. Bonchev Str., Bl. 105, Sofia-1113, BULGARIA
krat@bas.bg
Anthony Shannon
KvB Institute of Technology, North Sydney, 2060, AUSTRALIA
Warrane College, University of New South Wales, Kensington, 1465, AUSTRALIA
   (current: t.shannon@warrane.unsw.edu.au)
Presented at: 8th IWGN, Sofia, 26 June 2007
Published in: Conference proceedings, pages 48—55
Download:  PDF (120  Kb, File info)
Abstract: Using the apparatus of Generalized nets (GN) a GN model of a genetic algorithm is developed. The presented GN model describes the genetic algorithm search procedure based on the mechanism of natural selection. The GN model simultaneously evaluates several fitness functions, ranks the individuals according to their fitness and has the opportunity to choice the best fitness function regarding to specific problem domain.
Keywords: Generalized nets, Genetic algorithms, Fitness function
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