Domain transformation approach to deterministic optimization of examination timetables

Abdul Rahim, Siti; Bargiela, Andrzej; Qu, Rong

Abstract

In this paper we introduce a new optimization method for the examinations scheduling problem. Rather than attempting direct optimization of assignments of exams to specific time-slots, we perform permutations of slots and reassignments of exams upon the feasible (but not optimal) schedules obtained by the standard graph colouring method with Largest Degree ordering. The proposed optimization methods have been evaluated on the University of Toronto, University of Nottingham and International Timetabling Competition (ITC2007) datasets. It is shown that the proposed method delivers competitive results compared to other constructive methods in the timetabling literature on both the Nottingham and Toronto datasets, and it maintains the same optimization pattern of the solution improvement on the ITC2007 dataset. A deterministic pattern obtained for all benchmark datasets, makes the proposed method more understandable to the users.

Citation

Abdul Rahim, S., Bargiela, A., & Qu, R. (2013). Domain transformation approach to deterministic optimization of examination timetables. Artificial Intelligence Research, 2(1), https://doi.org/10.5430/air.v2n1p122

• Journal Article Type: Article
• Publication Date: Jan 1, 2013
• Deposit Date: Feb 26, 2015
• Publicly Available Date: Feb 26, 2015
• Journal: Artificial Intelligence Research
• Print ISSN: 1927-6974
• Electronic ISSN: 1927-6982
• Publisher: Sciedu Press
• Peer Reviewed: Peer Reviewed
• Volume: 2
• Issue: 1
• DOI: https://doi.org/10.5430/air.v2n1p122
• Keywords: Examination timetabling, Optimization, Slots permutations, Reassigning exams
• Public URL: https://nottingham-repository.worktribe.com/output/1003201
• Publisher URL: http://www.sciedu.ca/journal/index.php/air/article/view/1664