Adaptive linear combination of heuristic orderings in constructing examination timetables

Abdul-Rahman, Syariza; Bargiela, Andrzej; Burke, Edmund; �zcan, Ender; McCollum, Barry; McMullan, Paul

Abstract

In this paper, we investigate adaptive linear combinations of graph coloring heuristics with a heuristic modifier to address the examination timetabling problem. We invoke a normalisation strategy for each parameter in order to generalise the specific problem data. Two graph coloring heuristics were used in this study (largest degree and saturation degree). A score for the difficulty of assigning each examination was obtained from an adaptive linear combination of these two heuristics and examinations in the list were ordered based on this value. The examinations with the score value representing the higher difficulty were chosen for scheduling based on two strategies. We tested for single and multiple heuristics with and without a heuristic modifier with different combinations of weight values for each parameter on the Toronto and ITC2007 benchmark data sets. We observed that the combination of multiple heuristics with a heuristic modifier offers an effective way to obtain good solution quality. Experimental results demonstrate that our approach delivers promising results. We conclude that this adaptive linear combination of heuristics is a highly effective method and simple to implement.

Citation

Abdul-Rahman, S., Bargiela, A., Burke, E., Özcan, E., McCollum, B., & McMullan, P. (2014). Adaptive linear combination of heuristic orderings in constructing examination timetables. European Journal of Operational Research, 232(2), https://doi.org/10.1016/j.ejor.2013.06.052

• Journal Article Type: Article
• Publication Date: Jan 16, 2014
• Deposit Date: Sep 27, 2014
• Publicly Available Date: Sep 27, 2014
• Journal: European Journal of Operational Research
• Print ISSN: 0377-2217
• Electronic ISSN: 1872-6860
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 232
• Issue: 2
• DOI: https://doi.org/10.1016/j.ejor.2013.06.052
• Public URL: https://nottingham-repository.worktribe.com/output/721597
• Publisher URL: http://www.sciencedirect.com/science/article/pii/S0377221713005596
• Additional Information: NOTICE: this is the author’s version of a work that was accepted for publication in European Journal of Operational Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in European Journal of Operational Research, 232(2), (2014), doi: 10.1016/j.ejor.2013.06.052