prikaz prve stranice dokumenta PRIMJENA GENETSKIH ALGORITAMA
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master's thesis
PRIMJENA GENETSKIH ALGORITAMA
2020. urn:nbn:hr:143:251273
Vidić, Marko
Šibenik University of Applied Sciences
Management

Cite this document

Vidić, M. (2020). PRIMJENA GENETSKIH ALGORITAMA (Master's thesis). Šibenik: Šibenik University of Applied Sciences. Retrieved from https://urn.nsk.hr/urn:nbn:hr:143:251273

Vidić, Marko. "PRIMJENA GENETSKIH ALGORITAMA." Master's thesis, Šibenik University of Applied Sciences, 2020. https://urn.nsk.hr/urn:nbn:hr:143:251273

Vidić, Marko. "PRIMJENA GENETSKIH ALGORITAMA." Master's thesis, Šibenik University of Applied Sciences, 2020. https://urn.nsk.hr/urn:nbn:hr:143:251273

Vidić, M. (2020). 'PRIMJENA GENETSKIH ALGORITAMA', Master's thesis, Šibenik University of Applied Sciences, accessed 13 December 2024, https://urn.nsk.hr/urn:nbn:hr:143:251273

Vidić M. PRIMJENA GENETSKIH ALGORITAMA [Master's thesis]. Šibenik: Šibenik University of Applied Sciences; 2020 [cited 2024 December 13] Available at: https://urn.nsk.hr/urn:nbn:hr:143:251273

M. Vidić, "PRIMJENA GENETSKIH ALGORITAMA", Master's thesis, Šibenik University of Applied Sciences, Šibenik, 2020. Available at: https://urn.nsk.hr/urn:nbn:hr:143:251273

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Metadata
TitlePRIMJENA GENETSKIH ALGORITAMA
Title (english)THE APPLICATION OF GENETIC ALGORITHMS
AuthorMarko Vidić
MentorŽelimir Mikulić (mentor)
Committee memberDivna Goleš (predsjednik povjerenstva)
Committee memberGina Lugović (član povjerenstva)
Committee memberŽelimir Mikulić (član povjerenstva)
GranterŠibenik University of Applied Sciences
(Management)
Šibenik
Defense date and country2020-10-14, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
U ovom radu koristimo genetski algoritam kako bi pokušali riješiti nelinearni problem odabira namirnica uz zadana ograničenja. Pokušavamo zadovoljiti sve zadane nutritivne vrijednosti dok u isto vrijeme nastojimo minimizirati funkciju cilja. Koristimo brojna dodatna ograničenja kako bi problem učinili nelinearnim te promatramo kako se genetski algoritam u tome snalazi te da li može pružiti rješenje tamo gdje ostale metode ne mogu.
Abstract (english)
In this paper, we use a genetic algorithm to try and solve a nonlinear food selection problem with given constraints. We try to meet all the set nutritional values while at the same time trying to minimize the function of the target. We use a number of additional constraints to make the problem nonlinear, and we observe how the genetic algorithm handles it and whether it can provide a solution where other methods cannot.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:143:251273
Study programmeTitle: Management
Study programme type: professional
Study level: specialist graduate
Academic / professional title: stručni/a specijalist/specijalistica menadžmenta (stručni/a specijalist/specijalistica menadžmenta)
Type of resourceText
File originBorn digital
Access conditionsAccess restricted to students and staff of home institution
Terms of useLicence In copyright icon
Created on2020-10-16 07:21:42