Hybrid Variable Neighborhood HyperHeuristics for Exam Timetabling Problems
This paper presents our work on analysing the high level search within a graph based hyperheuristic. The graph based hyperheuristic solves the problem at a higher level by searching through permutations of graph heuristics rather than the actual solutions. The heuristic permutations are then used to...
| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Published: |
2005
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| Online Access: | https://eprints.nottingham.ac.uk/352/ |
| _version_ | 1848790397930700800 |
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| author | Qu, Rong Burke, Edmund |
| author_facet | Qu, Rong Burke, Edmund |
| author_sort | Qu, Rong |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | This paper presents our work on analysing the high level search within a graph based hyperheuristic. The graph based hyperheuristic solves the problem at a higher level by searching through permutations of graph heuristics rather than the actual solutions. The heuristic permutations are then used to construct the solutions. Variable Neighborhood Search, Steepest Descent, Iterated Local Search and Tabu Search are compared. An analysis of their performance within the high level search space of heuristics is also carried out. Experimental results on benchmark exam timetabling problems demonstrate the simplicity and efficiency of this hyperheuristic approach. They also indicate that the choice of the high level search methodology is not crucial and the high level search should explore the heuristic search space as widely as possible within a limited searching time. This simple and general graph based hyperheuristic may be applied to a range of timetabling and optimisation problems. |
| first_indexed | 2025-11-14T18:11:58Z |
| format | Conference or Workshop Item |
| id | nottingham-352 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T18:11:58Z |
| publishDate | 2005 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-3522020-05-04T20:30:57Z https://eprints.nottingham.ac.uk/352/ Hybrid Variable Neighborhood HyperHeuristics for Exam Timetabling Problems Qu, Rong Burke, Edmund This paper presents our work on analysing the high level search within a graph based hyperheuristic. The graph based hyperheuristic solves the problem at a higher level by searching through permutations of graph heuristics rather than the actual solutions. The heuristic permutations are then used to construct the solutions. Variable Neighborhood Search, Steepest Descent, Iterated Local Search and Tabu Search are compared. An analysis of their performance within the high level search space of heuristics is also carried out. Experimental results on benchmark exam timetabling problems demonstrate the simplicity and efficiency of this hyperheuristic approach. They also indicate that the choice of the high level search methodology is not crucial and the high level search should explore the heuristic search space as widely as possible within a limited searching time. This simple and general graph based hyperheuristic may be applied to a range of timetabling and optimisation problems. 2005 Conference or Workshop Item NonPeerReviewed Qu, Rong and Burke, Edmund (2005) Hybrid Variable Neighborhood HyperHeuristics for Exam Timetabling Problems. In: The Sixth Metaheuristics International Conference 2005, Aug, 2005, Vienna, Austria. |
| spellingShingle | Qu, Rong Burke, Edmund Hybrid Variable Neighborhood HyperHeuristics for Exam Timetabling Problems |
| title | Hybrid Variable Neighborhood HyperHeuristics
for Exam Timetabling Problems |
| title_full | Hybrid Variable Neighborhood HyperHeuristics
for Exam Timetabling Problems |
| title_fullStr | Hybrid Variable Neighborhood HyperHeuristics
for Exam Timetabling Problems |
| title_full_unstemmed | Hybrid Variable Neighborhood HyperHeuristics
for Exam Timetabling Problems |
| title_short | Hybrid Variable Neighborhood HyperHeuristics
for Exam Timetabling Problems |
| title_sort | hybrid variable neighborhood hyperheuristics
for exam timetabling problems |
| url | https://eprints.nottingham.ac.uk/352/ |