Hybrid Variable Neighborhood HyperHeuristicsfor Exam Timetabling Problems

Qu, Rong; Burke, Edmund

Abstract

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.

Citation

Qu, R., & Burke, E. (2005, August). Hybrid Variable Neighborhood HyperHeuristicsfor Exam Timetabling Problems. Paper presented at The Sixth Metaheuristics International Conference 2005, Vienna, Austria

• Presentation Conference Type: Conference Paper (unpublished)
• Conference Name: The Sixth Metaheuristics International Conference 2005
• Start Date: Aug 22, 2005
• End Date: Aug 26, 2005
• Publication Date: Jan 1, 2005
• Deposit Date: Dec 12, 2005
• Publicly Available Date: Oct 9, 2007
• Public URL: https://nottingham-repository.worktribe.com/output/1020572
• Contract Date: Dec 12, 2005