Genetic algorithm for multi objective optimization

dc.contributor.author	Polupan, Vladimir
dc.contributor.author	Cherednichenko, Galina
dc.date.accessioned	2016-12-23T09:40:04Z
dc.date.available	2016-12-23T09:40:04Z
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 for multi objective optimization / V. Polupan, G. Cherednichenko // Food Science for Well-being (CEFood 2016) : 8th Central European Congress on Food, 23–26 May 2016. – Kyiv : NUFT, 2016. – P. 105.	uk_UA
dc.identifier.uri	https://dspace.nuft.edu.ua/handle/123456789/24688
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 for multi objective optimization	uk_UA
dc.type	Thesis	uk_UA

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