Genetic algorithm for university course timetabling problem: application to a colombian college

Henao Ramírez, Diego; Restrepo Ramírez, John Fernando

dc.contributor.advisor	Gómez Jaramillo, Sebastián
dc.contributor.advisor	Parlaktuna, Mustafa
dc.contributor.author	Henao Ramírez, Diego
dc.contributor.author	Restrepo Ramírez, John Fernando
dc.date.accessioned	2022-11-03T19:54:42Z
dc.date.available	2022-11-03T19:54:42Z
dc.date.issued	2021-11-15
dc.identifier.uri	https://dspace.tdea.edu.co/handle/tdea/2337
dc.description.abstract	University Course Timetabling Problem (UCTP) is a type of scheduling problem with a set of events and constraints that will be satisfied. A commonly used concept to tackle this problem is the genetic algorithm, which intends to simulate the Darwinian theory of evolution and the survival of the fittest to generate a viable solution to a problem. In this thesis we adapted this concept to design a mathematical model, in order to implement it through the development of a software application to serve as a measure tool that would allow us to validate the relevance of a solution to try and solve the UCTP from the Tecnológico de Antioquia, using real data and its specific constraints.	spa
dc.format.extent	3 páginas	spa
dc.format.mimetype	application/pdf	spa
dc.language.iso	eng	spa
dc.publisher	Tecnológico de Antioquia, Institución Universitaria	spa
dc.rights	Tecnológico de Antioquia, Institución Universitaria, 2021	spa
dc.rights.uri	https://creativecommons.org/licenses/by-nc/4.0/	spa
dc.title	Genetic algorithm for university course timetabling problem: application to a colombian college
dc.type	Trabajo de grado - Pregrado	spa
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dcterms.references	Kohshori, M. S., & Abadeh, M. S. (2012). Hybrid Genetic Algorithms for University Course Timetabling. International Journal of Computer Science Issues, 9(2), 446–455.	spa
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dcterms.references	R.Sutar, S., & S. Bichkar, R. (2012). University Timetabling based on Hard Constraints using Genetic Algorithm. International Journal of Computer Applications, 42(15), 1–7. https://doi.org/10.5120/5765-7964	spa
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dcterms.references	Sigl, B., Golub, M., & Mornar, V. (2003). Solving timetable scheduling problem using genetic algorithms. Proceedings of the International Conference on Information Technology Interfaces, ITI, 519–524. https://doi.org/10.1109/ITI.2003.1225396	spa
dcterms.references	Timilsina, S., Negi, R., Khurana, Y., & Seth, J. (2015). Genetically Evolved Solution to Timetable Scheduling Problem. International Journal of Computer Applications, 114(18), 12–17. https://doi.org/10.5120/20077-2100	spa
dc.publisher.faculty	Facultad de Ingeniería	spa
dc.publisher.program	Ingenieria de Software	spa
dc.description.degreelevel	Pregrado	spa
dc.description.degreename	Ingeniero(a) de Software	spa
dc.publisher.place	Medellín	spa
dc.rights.accessrights	info:eu-repo/semantics/openAccess	spa
dc.rights.creativecommons	Atribución-NoComercial 4.0 Internacional (CC BY-NC 4.0)	spa
dc.subject.lemb	Algoritmos (Computadores)
dc.type.coar	http://purl.org/coar/resource_type/c_7a1f	spa
dc.type.content	Text	spa
dc.type.driver	info:eu-repo/semantics/bachelorThesis	spa
dc.type.redcol	https://purl.org/redcol/resource_type/TP	spa
dc.type.version	info:eu-repo/semantics/publishedVersion	spa
oaire.accessrights	http://purl.org/coar/access_right/c_abf2	spa
oaire.version	http://purl.org/coar/version/c_ab4af688f83e57aa	spa