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undergraduate thesis
Utjecaja parametara algoritma diferencijalne evolucije na njegovu učinkovitost
2025. urn:nbn:hr:200:449388
Turić, Kristijan
Josip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
Department of Software Engineering
Chair of Programming Languages and Systems

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Turić, K. (2025). Utjecaja parametara algoritma diferencijalne evolucije na njegovu učinkovitost (Undergraduate thesis). Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek. Retrieved from https://urn.nsk.hr/urn:nbn:hr:200:449388

Turić, Kristijan. "Utjecaja parametara algoritma diferencijalne evolucije na njegovu učinkovitost." Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2025. https://urn.nsk.hr/urn:nbn:hr:200:449388

Turić, Kristijan. "Utjecaja parametara algoritma diferencijalne evolucije na njegovu učinkovitost." Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2025. https://urn.nsk.hr/urn:nbn:hr:200:449388

Turić, K. (2025). 'Utjecaja parametara algoritma diferencijalne evolucije na njegovu učinkovitost', Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, accessed 26 February 2025, https://urn.nsk.hr/urn:nbn:hr:200:449388

Turić K. Utjecaja parametara algoritma diferencijalne evolucije na njegovu učinkovitost [Undergraduate thesis]. Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek; 2025 [cited 2025 February 26] Available at: https://urn.nsk.hr/urn:nbn:hr:200:449388

K. Turić, "Utjecaja parametara algoritma diferencijalne evolucije na njegovu učinkovitost", Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, Osijek, 2025. Available at: https://urn.nsk.hr/urn:nbn:hr:200:449388

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Metadata
TitleUtjecaja parametara algoritma diferencijalne evolucije na njegovu učinkovitost
Title (english)Impact of the parameters of differential evolution on its efficiency
AuthorKristijan Turić
MentorDražen Bajer (mentor)
Committee memberGoran Knežević (predsjednik povjerenstva)
Committee memberDražen Bajer (član povjerenstva)
Committee memberDamir Blažević (član povjerenstva)
GranterJosip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
(Department of Software Engineering)
(Chair of Programming Languages and Systems)
Osijek
Defense date and country2025-02-20, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Artificial Intelligence
Abstract
Ovaj rad bavi se istraživanjem diferencijalne evolucije, jednog od evolucijskih algoritama koji se pokazao vrlo učinkovit za probleme kontinuirane optimizacije. Rad uključuje analizu učinkovitosti algoritma diferencijalne evolucije pri različitim postavkama parametara. Parametri koje se postavljaju su veličina populacije, faktor skaliranja i stopa križanja. Detaljno su opisani parametri, te su navedene česte postavke istih. Opisuje se ostvareno programsko rješenje, te način rada samog rješenja. Eksperimentalna analiza provedena je na tri unimodalne i tri multimodalne funkcije, te su korištene dvije dimenzionalnosti u svrhu istraživanja ponašanja algoritma u rješavanju različitih problema. Analizirali su se rezultati, s posebnim fokusom na prosječne rezultate i standardne devijacije. Zaključno, rad pokazuje kako promjene u parametrima algoritma mogu utjecati na njegovu učinkovitost, te pruža smjernice o odabira postavki parametara ovisno o problemu.
Abstract (english)
This thesis investigates differential evolution, one of the evolutionary algorithms that has proven highly effective for continuous optimization problems. The paper includes an analysis of the efficiency of the differential evolution algorithm under various parameter settings. The parameters considered are population size, scaling factor, and crossover rate. The parameters are described in detail, and common settings are provided. The implemented software solution is described, as well as its functionality. The experimental analysis was conducted on three unimodal and three multimodal functions, with two different dimensionalities, in order to explore the algorithm's behavior in solving various problems. The results were analyzed with a particular focus on average outcomes and standard deviations. In conclusion, the thesis demonstrates how changes in the algorithm's parameters can affect its efficiency, and provides guidelines for selecting parameter settings depending on the problem.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:200:449388
Study programmeTitle: Undergraduate University Study Programme in Computer Engineering
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
Access conditionsOpen access
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Created on2025-02-26 07:10:32