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itec

Abstract:

We discuss, model and tackle two examination timetabling problems. The first is a real-world case while the latter is a well-known benchmark problem. Both are solved with the same hyper-heuristics approach. Unlike meta-heuristics, in which the search is executed on the space of solutions, hyper-heuristics operate on a search space of heuristics [Burke et al., 2003]. Hyper-heuristics were originally introduced for automating the low-level heuristics' selection, for example by applying machine learning techniques [Burke et al., 2008]. The low-level heuristics employed in both examination timetabling cases are built so that each of them can individually solve one specific part of the problem. By combining the low-level heuristics, the particular properties of each of them can be exploited to solve the problem.