Novel Hyper-heuristic Approaches in Exam Timetabling

This thesis presents an investigation into the use of hyper-heuristic approaches to construct and improve solutions for exam timetabling problems. The majority of the approaches developed in the literature operate on a space of potential solutions to a problem. However, a hyper-heuristic is a heuristic which acts on a space of heuristics, rather than a solution space directly. The majority of research papers, so far, have involved the design of tailored approaches which focus on tackling specific problems. Less well studied are hyper-heuristics which can operate on a range of problems. The first area of investigation is the use of a Greedy Random Adaptive Search Procedure to combine multiple heuristics within the construction of timetables. Different combinations of multiple heuristic orderings were examined, considering five graph-based heuristic orderings Largest Degree, Saturation Degree, Largest Enrolment, Largest Coloured Degree and Largest Weighted Degree. The development utilised two heuristic orderings simultaneously and subsequent development went on to break ties within the heuristic orderings. Improving exam timetables has been the subject of much research. It is generally the case that a meta-heuristic is used to improve constructed solutions. Indeed, there are usually a very large number of different methods