Genetic algorithm based examination timetabling system / Krishna Bacalso Hernandez.
Material type: TextLanguage: English Publication details: 2006Description: 92 leavesSubject(s): Dissertation note: Thesis (BS Computer Science) -- University of the Philippines Mindanao, 2006 Abstract: The genetic algorithm-based examination timetabling system was developed for creating feasible and acceptable final examination timetables for the undergraduate degree programs of the University of the Philippines in Mindanao. It responds to the need of the university on handling an increasing occurrence of conflict in producing final examination timetables due to the increasing number of students in the university and the implementation of the revised general education program (RGEP). The developed system generates batched timetables for further analysis and selection where the details of constraint violation are described. The use of genetic algorithm is described in detail to further illustrate the functionality of the system. Genetic algorithm is used both in generating initial feasible timetables and in optimization to create acceptable timetables.Cover image | Item type | Current library | Collection | Call number | Status | Date due | Barcode |
---|---|---|---|---|---|---|---|
|
Thesis | University Library General Reference | Room-Use Only | LG993.5 2006 C6 H47 (Browse shelf(Opens below)) | Not For Loan | 3UPML00011753 | |
|
Thesis | University Library Archives and Records | Preservation Copy | LG993.5 2006 C6 H47 (Browse shelf(Opens below)) | Not For Loan | 3UPML00031331 |
Thesis (BS Computer Science) -- University of the Philippines Mindanao, 2006
The genetic algorithm-based examination timetabling system was developed for creating feasible and acceptable final examination timetables for the undergraduate degree programs of the University of the Philippines in Mindanao. It responds to the need of the university on handling an increasing occurrence of conflict in producing final examination timetables due to the increasing number of students in the university and the implementation of the revised general education program (RGEP). The developed system generates batched timetables for further analysis and selection where the details of constraint violation are described. The use of genetic algorithm is described in detail to further illustrate the functionality of the system. Genetic algorithm is used both in generating initial feasible timetables and in optimization to create acceptable timetables.
There are no comments on this title.