Issue:Generalized net models of crossover operators in genetic algorithms

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Title of paper: A generalized net model of a mutation operator for the breeder genetic algorithm Author(s): Tania Pencheva Centre of Biomedical Engineering – Bulgarian Academy of Sciences, 105, Acad. G. Bonchev Str., Sofia 1113, Bulgaria tania.pencheva@clbme.bas.bg Olympia Roeva Centre of Biomedical Engineering – Bulgarian Academy of Sciences, 105, Acad. G. Bonchev Str., Sofia 1113, Bulgaria olympia@clbme.bas.bg Anthony Shannon Raffles College of Design and Commerce, North Sydney, 2060, Australia Warrane College, University of New South Wales, Kensington, 1465, Australia tonySHANNON@raffles.edu.au , tony@warrane.unsw.edu.au Presented at: 9th IWGN, Sofia, 4 July 2008 Published in: Conference proceedings, pages 64—70 Download:  PDF (174  Kb, File info) Abstract: The apparatus of Generalized nets is here applied to a description of different techniques of crossover, which is one of the basic genetic algorithm operators. Presented here are GN models which describe three crossover techniques, namely one-point, two-point crossover as well as the “cut and splice” technique. The resulting GN models can be considered as separate modules, but they can also be accumulated into a GN model to describe a whole genetic algorithm. Keywords: Generalized nets, Genetic algorithms, Crossover References: Aladjov H., K. Atanassov, A Generalized Net for Genetic Algorithms Learning, Proc. of the XXX Spring Conference of the Union of Bulgarian Mathematicians, Borovets, 2001, 242-249. Atanassov K., Generalized Nets and Systems Theory, Sofia, Academic Publishing House “Prof. M. Drinov”, 1997. Atanassov K., Generalized Nets, Singapore, New Jersey, London, World Scientific, 1991. Atanassov K., H. Aladjov, Generalized Nets in Artificial Intelligence, Vol. 2: Generalized nets and Machine Learning, Prof. M. Drinov Academic Publishing House, Sofia, 2000. Bies R.; M. Muldoon, B. Pollock, S. Manuck, G. Smith, M. Sale, A Genetic Algorithm-based, Hybrid Machine Learning Approach to Model Selection, Journal of Pharmacokinetics and Pharmacodynamics, 2006, 196-221. Chipperfield A., P. J. Fleming, H. Pohlheim, C. M. Fonseca, Genetic Algorithm Toolbox for use with MATLAB, 1993. Davis L., Handbook of genetic algorithms, Van Nostrand Reinhold, 1991. Fogel D., Evolutionary Computation: Toward a New Philosophy of Machine Intelligence, IEEE Press, NJ, Third edition, 2006. Goldberg D. E., Genetic Algorithms in Search, Optimization and Machine Learning, Addison Wesley, 1989. Holland J., Adaptation in Natural and Artificial Systems, University of Michigan Press, Ann Arbor, 1975. Roeva О., K. Atanassov, A. Shannon, Generalized Net for Selection of Genetic Algorithm Operators, Proceedings of Scientific Session of the Section “Informatics”, Union of Scientists in Bulgaria, in press. Roeva O., K. Atanassov, A. Shannon, Generalized net for evaluation of genetic algorithm fitness function, Proceedings of the Eighth International Workshop on Generalized Nets, Sofia, June 26, 2007, 48-55. Citations: Issue:Modelling of a stochastic universal sampling selection operator in genetic algorithms using generalized nets ‎ (← links) Issue:Generalized net model of intuitionistic fuzzy logic control of genetic algorithm parameters ‎ (← links) The list of publications, citing this article may be empty or incomplete. If you can provide relevant data, please, write on the talk page.