Edmund Burke
Hybrid Graph Heuristics within a Hyper-heuristic Approach to Exam Timetabling Problems
Burke, Edmund; Dror, Moshe; Petrovic, Sanja; Qu, Rong
Authors
Moshe Dror
SANJA PETROVIC SANJA.PETROVIC@NOTTINGHAM.AC.UK
Professor of Operational Research
RONG QU rong.qu@nottingham.ac.uk
Professor of Computer Science
Contributors
B.L. Golden
Editor
S. Raghavan
Editor
E.A. Wasil
Editor
Abstract
This paper is concerned with the hybridization of two graph coloring heuristics (Saturation Degree and Largest Degree), and their application within a hyperheuristic for exam timetabling problems. Hyper-heuristics can be seen as algorithms which intelligently select appropriate algorithms/heuristics for solving a problem. We developed a Tabu Search based hyper-heuristic to search for heuristic lists (of graph heuristics) for solving problems and investigated the heuristic lists found by employing knowledge discovery techniques. Two hybrid approaches (involving Saturation Degree and Largest Degree) including one which employs Case Based Reasoning are presented and discussed. Both the Tabu Search based hyper-heuristic and the hybrid approaches are tested on random and real-world exam timetabling problems. Experimental results are comparable with the best state-of-the-art approaches (as measured against established benchmark problems). The results also demonstrate an increased level of generality in our approach.
Citation
Burke, E., Dror, M., Petrovic, S., & Qu, R. (2005). Hybrid Graph Heuristics within a Hyper-heuristic Approach to Exam Timetabling Problems. In B. Golden, S. Raghavan, & E. Wasil (Eds.), The Next Wave in Computing, Optimization, and Decision Technologies. Springer
Publication Date | Jan 1, 2005 |
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Deposit Date | Dec 12, 2005 |
Publicly Available Date | Oct 9, 2007 |
Peer Reviewed | Peer Reviewed |
Book Title | The Next Wave in Computing, Optimization, and Decision Technologies |
Keywords | case based reasoning, exam timetabling problems, graph heuristics, hyperheuristics,knowledge discovery, tabu search |
Public URL | https://nottingham-repository.worktribe.com/output/1020188 |
Files
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