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Gene pool recombination, genetic algorithm, and the onemax function

Heinz Muhlenbein ; GMO Forschungszentrum lnformationstechnik, SET.AS, Schloss Birlinghoven, Sankt Augustin, Germany
Uday K. Chakraborty ; Department of Computer Science and Engineering, Jadavpur University, Calcutta 700 032, India

Puni tekst: engleski, pdf (7 MB) str. 167-182 preuzimanja: 219* citiraj
APA 6th Edition
Muhlenbein, H. i Chakraborty, U.K. (1997). Gene pool recombination, genetic algorithm, and the onemax function. Journal of computing and information technology, 5 (3), 167-182. Preuzeto s https://hrcak.srce.hr/150258
MLA 8th Edition
Muhlenbein, Heinz i Uday K. Chakraborty. "Gene pool recombination, genetic algorithm, and the onemax function." Journal of computing and information technology, vol. 5, br. 3, 1997, str. 167-182. https://hrcak.srce.hr/150258. Citirano 08.08.2020.
Chicago 17th Edition
Muhlenbein, Heinz i Uday K. Chakraborty. "Gene pool recombination, genetic algorithm, and the onemax function." Journal of computing and information technology 5, br. 3 (1997): 167-182. https://hrcak.srce.hr/150258
Harvard
Muhlenbein, H., i Chakraborty, U.K. (1997). 'Gene pool recombination, genetic algorithm, and the onemax function', Journal of computing and information technology, 5(3), str. 167-182. Preuzeto s: https://hrcak.srce.hr/150258 (Datum pristupa: 08.08.2020.)
Vancouver
Muhlenbein H, Chakraborty UK. Gene pool recombination, genetic algorithm, and the onemax function. Journal of computing and information technology [Internet]. 1997 [pristupljeno 08.08.2020.];5(3):167-182. Dostupno na: https://hrcak.srce.hr/150258
IEEE
H. Muhlenbein i U.K. Chakraborty, "Gene pool recombination, genetic algorithm, and the onemax function", Journal of computing and information technology, vol.5, br. 3, str. 167-182, 1997. [Online]. Dostupno na: https://hrcak.srce.hr/150258. [Citirano: 08.08.2020.]

Sažetak
In this paper we present an analysis of gene pool recombination in genetic algorithms in the context of the onemax function. We have developed a Markov chain framework for computing the probability of convergence, and have shown how the analysis can be used to estimate the critical population size. The Markov model is used to investigate drift in the multiple-loci case. Additionally, we have estimated the minimum population size needed for optimality, and recurrence relations describing the growth of the advantageous allele in the infinite-population case have been derived. Simulation results are presented.

Ključne riječi
Genetic algorithm; gene pool recombination; onemax function; Markov chain; convergence

Hrčak ID: 150258

URI
https://hrcak.srce.hr/150258

Posjeta: 263 *