Genetički algoritmi za probleme satnice

Sigl, Branimir

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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

Cite this document

APA 6th Edition

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

MLA 8th Edition

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

Chicago 17th Edition

Harvard

Sigl, B. (2004). 'Genetički algoritmi za probleme satnice', Scientific master's theses, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 25 April 2024, https://urn.nsk.hr/urn:nbn:hr:168:384518

Vancouver

Sigl B. Genetički algoritmi za probleme satnice [Scientific master's theses]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2004 [cited 2024 April 25] Available at: https://urn.nsk.hr/urn:nbn:hr:168:384518

IEEE

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

Cite this item: https://urn.nsk.hr/urn:nbn:hr:168:384518

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Metadata

Title	Genetički algoritmi za probleme satnice
Author	Branimir Sigl
Mentor	Vedran Mornar (mentor)
Committee member	Leo Budin (predsjednik povjerenstva)
Committee member	Vedran Mornar (član povjerenstva)
Committee member	Luka Neralić (član povjerenstva)
Granter	University of Zagreb Faculty of Electrical Engineering and Computing (Department of Applied Mathematics) Zagreb
Defense date and country	2004-10-22, 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)
Language	croatian
URN:NBN	urn:nbn:hr:168:384518
Study programme	Title: Postgraduate master programe in computing Study programme type: university Study level: postgraduate Academic / professional title: magistar inženjer računarstva (magistar inženjer računarstva)
Type of resource	Text
File origin	Born digital
Access conditions	Closed access
Terms of use
Repository	FER Repository
Created on	2019-06-12 13:07:49

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