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undergraduate thesis
Primjena genetskih algoritama u umjetnoj inteligenciji
2017. urn:nbn:hr:166:153110
Celio Cega, Matko
University of Split
Faculty of Science
Department of Informatics

Cite this document

Celio Cega, M. (2017). Primjena genetskih algoritama u umjetnoj inteligenciji (Undergraduate thesis). Split: University of Split, Faculty of Science. Retrieved from https://urn.nsk.hr/urn:nbn:hr:166:153110

Celio Cega, Matko. "Primjena genetskih algoritama u umjetnoj inteligenciji." Undergraduate thesis, University of Split, Faculty of Science, 2017. https://urn.nsk.hr/urn:nbn:hr:166:153110

Celio Cega, Matko. "Primjena genetskih algoritama u umjetnoj inteligenciji." Undergraduate thesis, University of Split, Faculty of Science, 2017. https://urn.nsk.hr/urn:nbn:hr:166:153110

Celio Cega, M. (2017). 'Primjena genetskih algoritama u umjetnoj inteligenciji', Undergraduate thesis, University of Split, Faculty of Science, accessed 06 November 2024, https://urn.nsk.hr/urn:nbn:hr:166:153110

Celio Cega M. Primjena genetskih algoritama u umjetnoj inteligenciji [Undergraduate thesis]. Split: University of Split, Faculty of Science; 2017 [cited 2024 November 06] Available at: https://urn.nsk.hr/urn:nbn:hr:166:153110

M. Celio Cega, "Primjena genetskih algoritama u umjetnoj inteligenciji", Undergraduate thesis, University of Split, Faculty of Science, Split, 2017. Available at: https://urn.nsk.hr/urn:nbn:hr:166:153110

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Metadata
TitlePrimjena genetskih algoritama u umjetnoj inteligenciji
Title (english)Application of genetic algorithms in artificial intelligence
AuthorMatko Celio Cega
MentorSaša Mladenović (mentor)
Committee memberSaša Mladenović (predsjednik povjerenstva)
Committee memberGoran Zaharija (član povjerenstva)
Committee memberDivna Krpan (član povjerenstva)
GranterUniversity of Split
Faculty of Science
(Department of Informatics)
Split
Defense date and country2017-07-07, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Cilj rada je opisati princip rada genetskih algoritama te njihovu primjenu na konkretnom primjeru problema. U radu su opisana dva genetska algoritma: algoritam usamljenog mutanta te algoritam čvrstog stanja. U algoritmima su se koristili različiti genetski operatori selekcije, mutacije i križanja kromosoma (koji predstavljaju rješenje problema)u populaciji. Osim genetskih algoritama, korišten je i algoritam sirove snage te je uspoređeno vrijeme izvođenja oba algoritma. Problem rješen u ovom radu je problem ruksaka, kombinatorni problem smještanja određenog broja predmeta u “ruksak” fiksnog kapaciteta. Ima čestu primjenu u kombinatorici i računarstvu te je logičan izbor problema za rješavanje algoritmima koji tek odnedavno počinju dobijati na popularnosti. Nakon implementacije problema programskim jezikom C#, testiranja su pokazala da genetski algoritmi daju “dovoljno dobro” rješenje u vrlo prihvatljivom vremenu te su odličan odabir algoritama za one probleme kojima je važnija brzina izvođenja, a ne odabir baš onog najboljeg mogućeg rješenja.
Abstract (english)
The aim of the thesis is to describe the principle of genetic algorithms and their application in a concrete example of a problem. Two genetic algorithms are described: lonely mutant algorithm and steady state algorithm.In the algorithms, different examples of genetic operators (selection, mutation and crossover) were used to operate over chrommosomes (representation of solution of the problem) in population. In addition to genetic algorithms, a brute force algorithm was used, and the time of running both algorithms was compared. Problem solved in this thesis was knapsack problem, combinatorial problem of placing a certain number of items in a “knapsack” of fixed capacity. It has frequent use in combinatorics an computer science and it is logical choice of problem to solve with algorithms that have recently began to gain popularity. After implementation of problem with C# programming language, tests have shown that genetic algorithms provide a “good enough” solution in very acceptable time and are excellent choice of algorithms for problems where the speed is more important than finding exactly the best solution.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:166:153110
Study programmeTitle: Mathematics and Computer Science
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/prvostupnica (baccalaureus/baccalaurea) matematike i informatike (sveučilišni/a prvostupnik/prvostupnica (baccalaureus/baccalaurea) matematike i informatike)
Type of resourceText
File originBorn digital
Access conditionsAccess restricted to students and staff of home institution
Terms of useLicence In copyright icon
Created on2018-04-13 16:46:06