Solving Toronto Examination Timetabling Using Heuristic Method

The examination timetabling problem has attracted the interested of many researchers over the years. However, this problem is difficult to solve due to the lack of benchmark dataset and many constraints that need to be satisfied in examination timetabling problem. Toronto benchmark data contains 13...

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Bibliographic Details
Main Author: Lim Ruey, Long
Format: Undergraduates Project Papers
Language:English
Published: 2013
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/7253/
http://umpir.ump.edu.my/id/eprint/7253/
http://umpir.ump.edu.my/id/eprint/7253/1/CD7618.pdf
Description
Summary:The examination timetabling problem has attracted the interested of many researchers over the years. However, this problem is difficult to solve due to the lack of benchmark dataset and many constraints that need to be satisfied in examination timetabling problem. Toronto benchmark data contains 13 real-world examination timetabling problem which have different conflict density for every dataset. Many researchers solved Toronto benchmark data using different method in order to produce a timetable which is feasible and solve all the constraints. To produce a feasible examination timetable, all the exams need to be scheduled into timeslot while satisfying the hard constraint and soft constraint. The timetable result should have the minimum penalty value in term of spread exams. Therefore, the technique partial graph heuristic with hill climbing method should be implemented to solve Toronto examination timetabling problem. The graph heuristic method will partially schedule the exam and then improved by hill climbing method. This process will be repeated until all the exams are scheduled. By using this technique, the solution of timetable result can comply all of the constraints and has a competitive result compared to other researchers' result.