hrcak mascot   Srce   HID

Original scientific paper

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

Fulltext: english, pdf (7 MB) pages 167-182 downloads: 193* cite
APA 6th Edition
Muhlenbein, H. & Chakraborty, U.K. (1997). Gene pool recombination, genetic algorithm, and the onemax function. Journal of computing and information technology, 5 (3), 167-182. Retrieved from https://hrcak.srce.hr/150258
MLA 8th Edition
Muhlenbein, Heinz and Uday K. Chakraborty. "Gene pool recombination, genetic algorithm, and the onemax function." Journal of computing and information technology, vol. 5, no. 3, 1997, pp. 167-182. https://hrcak.srce.hr/150258. Accessed 29 Mar. 2020.
Chicago 17th Edition
Muhlenbein, Heinz and Uday K. Chakraborty. "Gene pool recombination, genetic algorithm, and the onemax function." Journal of computing and information technology 5, no. 3 (1997): 167-182. https://hrcak.srce.hr/150258
Harvard
Muhlenbein, H., and Chakraborty, U.K. (1997). 'Gene pool recombination, genetic algorithm, and the onemax function', Journal of computing and information technology, 5(3), pp. 167-182. Available at: https://hrcak.srce.hr/150258 (Accessed 29 March 2020)
Vancouver
Muhlenbein H, Chakraborty UK. Gene pool recombination, genetic algorithm, and the onemax function. Journal of computing and information technology [Internet]. 1997 [cited 2020 March 29];5(3):167-182. Available from: https://hrcak.srce.hr/150258
IEEE
H. Muhlenbein and U.K. Chakraborty, "Gene pool recombination, genetic algorithm, and the onemax function", Journal of computing and information technology, vol.5, no. 3, pp. 167-182, 1997. [Online]. Available: https://hrcak.srce.hr/150258. [Accessed: 29 March 2020]

Abstracts
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.

Keywords
Genetic algorithm; gene pool recombination; onemax function; Markov chain; convergence

Hrčak ID: 150258

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

Visits: 233 *