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Adaptive linear combination of heuristic orderings in constructing examination timetables

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

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Authors

Syariza Abdul-Rahman

Andrzej Bargiela

Edmund Burke

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ENDER OZCAN ender.ozcan@nottingham.ac.uk
Professor of Computer Science and Operational Research

Barry McCollum

Paul McMullan



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 Mar 28, 2024
Journal European Journal of Operational Research
Print ISSN 0377-2217
Electronic ISSN 0377-2217
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

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