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scientific master's theses
Genetički algoritmi za probleme satnice
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2004. urn:nbn:hr:168:384518
Sigl, Branimir
University of Zagreb
Faculty of Electrical Engineering and Computing
Department of Applied Mathematics

Institutional repository: FER Repository

Cite this document

Sigl, B. (2004). Genetički algoritmi za probleme satnice (Scientific master's theses). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:384518

Sigl, Branimir. "Genetički algoritmi za probleme satnice." Scientific master's theses, University of Zagreb, Faculty of Electrical Engineering and Computing, 2004. https://urn.nsk.hr/urn:nbn:hr:168:384518

Sigl, Branimir. "Genetički algoritmi za probleme satnice." Scientific master's theses, University of Zagreb, Faculty of Electrical Engineering and Computing, 2004. https://urn.nsk.hr/urn:nbn:hr:168:384518

Sigl, B. (2004). 'Genetički algoritmi za probleme satnice', Scientific master's theses, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 04 November 2024, https://urn.nsk.hr/urn:nbn:hr:168:384518

Sigl B. Genetički algoritmi za probleme satnice [Scientific master's theses]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2004 [cited 2024 November 04] Available at: https://urn.nsk.hr/urn:nbn:hr:168:384518

B. Sigl, "Genetički algoritmi za probleme satnice", Scientific master's theses, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2004. Available at: https://urn.nsk.hr/urn:nbn:hr:168:384518

Metadata
TitleGenetički algoritmi za probleme satnice
AuthorBranimir Sigl
MentorVedran Mornar (mentor)
Committee memberLeo Budin (predsjednik povjerenstva)
Committee memberVedran Mornar (član povjerenstva)
Committee memberLuka Neralić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
(Department of Applied Mathematics)
Zagreb
Defense date and country2004-10-22, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Universal decimal classification
(UDC)		004 - Computer science and technology. Computing. Data processing
Abstract
Usprkos raširenosti problema rasporeda sati, ne postoji jedinstveno programsko rješenje prilagođeno svim institucijama. Programsko rješenje i genetički algoritam predstavljeni u ovom radu koriste se za izradu rasporeda sati fakulteta i srednjih škola. Predloženi genetički algoritam provjeren je na više podskupova podataka Fakulteta elektrotehnike i računarstva u Zagrebu, te skupu problema Ekonomske i birotehničke škole u Bjelovaru. Osnovni genetički algoritam je zbog brže konvergencije prema rješenju u ovom radu proširen metodama lokalnog pretraživanja i rekurzivnim algoritmom usmjerenog pretraživanja. Rekurzivni algoritam posebno je prilagođen radu sa strukturama genetičkog algoritma. Dobiveno rješenje poboljšano je posebnim metodama optimizacije nad glomaznim strukturama genetičkog algoritma. Programsko rješenje implementirano je u paketu Microsoft Visual Studio.NET - programski jezik C#. Genetički algoritam je zbog brzine rada izveden u programskom jeziku C++. Kao relacijska baza podataka korišten je Microsoft Office Access. U prvih nekoliko poglavlja govori se o općem problemu raspoređivanja u sklopu kojeg je dan pregled tehnika rješavanja problema raspoređivanja. Opći dio govori i o formulacijama problema rasporeda sati, te općenito o genetičkim algoritmima. U središnjem dijelu rada govori se o načinu rješavanja problema rasporeda sati pomoću genetičkog algoritma, te o problemima sa kojima se susretalo u izradi ovog rada. Detaljno su opisane cjeline koje su pomogle efikasnom rješavanju postavljenog problema. Posljednja poglavlja predstavljaju dobivene rezultate i analizu rješenja potkrijepljenu grafovima.
Abstract (english)
Despite of popularity of timetable scheduling problems, there is no common program solution suitable for all institutions. Program solution and genetic algorithm presented in this thesis are used to produce university and high school timetables. Presented genetic algorithm is tested on multiple data sets of Faculty of Engineering and Computing in Zagreb and School of Economics in Bjelovar. In this thesis the common genetic algorithm is broadened by local search methods to establish faster solution convergence. A recursive directed search algorithm is specially adopted for work with genetic algorithms structures. The solution is improved with special optimization techniques presented on the huge genetic algorithm structures. The program solution is developed in Microsoft Visual Studio.NET IDE - program language C#. The genetic algorithm is developed in C++ due to algorithm speed issues. Microsoft Office Access is used as relational database. In the first few chapters general scheduling problems are described. The survey of timetable scheduling techniques is also given. This part also presents some known formulations of timetable scheduling problem. In the central part of the thesis ways of solving of timetable scheduling problem using genetic algorithms are described and problems which came across. Last few chapters present obtained results and solution analysis fortified with graphs.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:384518
Study programmeTitle: Postgraduate master programe in computing
Study programme type: university
Study level: postgraduate
Academic / professional title: magistar inženjer računarstva (magistar inženjer računarstva)
Type of resourceText
File originBorn digital
Access conditionsClosed access
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Created on2019-06-12 13:07:49