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Issue:Modelling of a stochastic universal sampling selection operator in genetic algorithms using generalized nets

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Title of paper: Modelling of a stochastic universal sampling selection operator in genetic algorithms using generalized nets
Author(s):
Tania Pencheva
Centre of Biomedical Engineering, Bulgarian Academy of Sciences, 105 Acad. G. Bonchev Str., 1113 Sofia, Bulgaria
tania.pencheva@clbme.bas.bg
Krassimir Atanassov
Centre of Biomedical Engineering, Bulgarian Academy of Sciences, 105 Acad. G. Bonchev Str., 1113 Sofia, Bulgaria
krat@bas.bg
Anthony Shannon
Warrane College, University of New South Wales, Kensington, 1465, Australia
t.shannon@warrane.unsw.edu.au
Presented at: 10th IWGN, Sofia, 5 December 2009
Published in: Conference proceedings, pages 1—7
Download:  PDF (209  Kb, Info)
Abstract: The apparatus of Generalized Nets (GNs) is applied here to a description of a selection operator, which is one of the basic genetic algorithm operators. The GN model presented here describes one of the most widely used selection algorithms in current GA, namely stochastic universal sampling. The resulting GN model could be considered as a separate module, but can also be accumulated into a GN model to describe a whole genetic algorithm.
Keywords: Generalized nets, Genetic algorithms, Selection, Stochastic universal sampling
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