Incorporating great deluge with kempe chain neighbourhood structure for the enrolment-based course timetabling problem

Authors:
Salwani Abdullah;Khalid Shaker;Barry McCollum;Paul McMullan
Affiliations:
Data Mining and Optimization Research Group, Center for Artificial Intelligence Technology, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia;Data Mining and Optimization Research Group, Center for Artificial Intelligence Technology, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia;Department of Computer Science, Queen's University Belfast, Belfast, United Kingdom;Department of Computer Science, Queen's University Belfast, Belfast, United Kingdom
Venue:
RSKT'10 Proceedings of the 5th international conference on Rough set and knowledge technology
Year:
2010

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Abstract

In general, course timetabling refers to assignment processes that assign events (courses) to a given rooms and timeslots subject to a list of hard and soft constraints. It is a challenging task for the educational institutions. In this study we employed a great deluge algorithm with kempe chain neighbourhood structure as an improvement algorithm. The Round Robin (RR) algorithm is used to control the selection of neighbourhood structures within the great deluge algorithm. The performance of our approach is tested over eleven benchmark datasets (representing one large, five medium and five small problems). Experimental results show that our approach is able to generate competitive results when compared with previous available approaches. Possible extensions upon this simple approach are also discussed.