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Genetic Algorithms:Case study SUST Timetable

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dc.contributor.author Ahmed, Zuhal Hamad
dc.contributor.author supervisor - mohammed khider Co-supervisor - Abdalgfar hamed
dc.date.accessioned 2014-10-21T08:30:29Z
dc.date.available 2014-10-21T08:30:29Z
dc.date.issued 2005-12-01
dc.identifier.citation Ahmed,Zuhal Hamad,Genetic Algorithms(Case study SUST Timetable)/Zuhal Hamad Ahmed ;Mohamed Khider,Abd ElGhafar HamedKhartoum:Sudan University of Science and Technology,College of Computer Science and Information Technology,2005..-142p.:ill.;28cm.-M.sc en_US
dc.identifier.uri http://repository.sustech.edu/handle/123456789/7393
dc.description Thesis en_US
dc.description.abstract The timetabling problem comes up every year in educational institutions, which has been solved by human resources for a long time. The problem is a special version of the optimization problems, it is computationally NP-hard, although, there are some attempts to apply computer based methods, their use is limited by the problem’s complexity, and therefore Genetic Algorithms were applied, because they are robust enough in such a huge problem space. The project offers a system for University course timetabling based on the use of Genetic Algorithms. The system has two types of users; normal user who can only view the timetable (lecturer timetable, class timetable, and classroom timetable), and administrator user who has full control of the system- the system should verify him. Each type of users are provided by an interactive user interface. The system is web based and can be accessed via the Internet. The administrator user is the only one who can create a timetable for a particular class. In creating timetable the use of genetic algorithm is occurred. The use of genetic algorithm require many component: declaring the problem’s specific constraints, constructing a problem’s specific evaluation function (fitness function), the type of the representation of the solution (chromosome) used, and the genetic algorithm parameters also must be determined. In this thesis the type of genetic algorithm used is the simple genetic algorithm. Problems tested here are based on real data from the college of computer science. en_US
dc.description.sponsorship Sudan University of Science and Technology en_US
dc.language.iso en en_US
dc.publisher Sudan University of Science and Technology en_US
dc.subject Genetic Algorithms en_US
dc.subject SUST Timetable en_US
dc.subject Computer Science en_US
dc.title Genetic Algorithms:Case study SUST Timetable en_US
dc.title.alternative الخوارزميات الجينية ( حالة الدراسة العلمية الجدول الزمني ) en_US
dc.type Thesis en_US


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