Genetic algorithm in optimization tasks

dc.contributor.author	Polupan, Vladimir
dc.contributor.author	Cherednichenko, Galina
dc.date.accessioned	2016-12-23T09:42:29Z
dc.date.available	2016-12-23T09:42:29Z
dc.date.issued	2016
dc.description.abstract	Many, if not most, optimization problems have multiple objectives. Historically, multiple objectives have been combined ad hoc to form a scalar objective function, usually through a linear combination (weighted sum) of the multiple attributes, or by turning objectives into constraints.	uk_UA
dc.identifier.citation	Polupan, V. Genetic algorithm in optimization tasks / V. Polupan, G. Cherednichenko // Youth scientific achievements to the 21st century nutrition problem solution : 82 International scientific conference of young scientist and students, 13–14 April 2016. – Part 4. – Kyiv : NUFT, 2016. – P. 206.	uk_UA
dc.identifier.uri	https://dspace.nuft.edu.ua/handle/123456789/24689
dc.language.iso	other	uk_UA
dc.subject	programming	uk_UA
dc.subject	genetic algorithms	uk_UA
dc.subject	програмування	uk_UA
dc.subject	генетичні алгоритми	uk_UA
dc.subject	программирование	uk_UA
dc.subject	генетические алгоритмы	uk_UA
dc.subject	кафедра автоматизації та комп'ютерних технологій систем управління ім. проф. А.П. Ладанюка	uk_UA
dc.title	Genetic algorithm in optimization tasks	uk_UA
dc.type	Thesis	uk_UA

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