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https://doi.org/10.2498/cit.2003.03.07

Evolutionary Timetabling Using Biased Genetic Operators

Daniel Danciu

Puni tekst: engleski, pdf (159 KB) str. 193-199 preuzimanja: 439* citiraj
APA 6th Edition
Danciu, D. (2003). Evolutionary Timetabling Using Biased Genetic Operators. Journal of computing and information technology, 11 (3), 193-199. https://doi.org/10.2498/cit.2003.03.07
MLA 8th Edition
Danciu, Daniel. "Evolutionary Timetabling Using Biased Genetic Operators." Journal of computing and information technology, vol. 11, br. 3, 2003, str. 193-199. https://doi.org/10.2498/cit.2003.03.07. Citirano 24.02.2020.
Chicago 17th Edition
Danciu, Daniel. "Evolutionary Timetabling Using Biased Genetic Operators." Journal of computing and information technology 11, br. 3 (2003): 193-199. https://doi.org/10.2498/cit.2003.03.07
Harvard
Danciu, D. (2003). 'Evolutionary Timetabling Using Biased Genetic Operators', Journal of computing and information technology, 11(3), str. 193-199. https://doi.org/10.2498/cit.2003.03.07
Vancouver
Danciu D. Evolutionary Timetabling Using Biased Genetic Operators. Journal of computing and information technology [Internet]. 2003 [pristupljeno 24.02.2020.];11(3):193-199. https://doi.org/10.2498/cit.2003.03.07
IEEE
D. Danciu, "Evolutionary Timetabling Using Biased Genetic Operators", Journal of computing and information technology, vol.11, br. 3, str. 193-199, 2003. [Online]. https://doi.org/10.2498/cit.2003.03.07

Sažetak
Evolutionary Algorithms have proved to be a flexible and effective technique for addressing various instances of the timetabling problem. This article describes an investigation and its results on an evolutionary approach to solving a particular class of highly constrained timetabling problems. The convergence speed of the evolution program has been significantly improved with the usage of biased operators, which generate offspring by preserving the building blocks of the parents. We also describe two metrics for measuring the efficiency of the genetic operators and how convergence speed has been improved by applying these metrics to fine-tune the probability of the genetic operators. Computational experiments over real test problems showed promising results.

Hrčak ID: 44746

URI
https://hrcak.srce.hr/44746

Posjeta: 564 *