Examination timetabling using late acceptance hyper-heuristics

A hyperheuristic is a high level problem solving methodology that performs a search over the space generated by a set of low level heuristics. One of the hyperheuristic frameworks is based on a single point search containing two main stages: heuristic selection and move acceptance. Most of the existing move acceptance methods compare a new solution, generated after applying a heuristic, against a current solution in order to decide whether to reject it or replace the current one. Late acceptance strategy is presented as a promising local search methodology based on a novel move acceptance mechanism. This method performs a comparison between the new candidate solution and a previous solution that is generated L steps earlier. In this study, the performance of a set of hyper-heuristics utilising different heuristic selection methods combined with the late acceptance strategy are investigated over an examination timetabling problem. The results illustrate the potential of this approach as a hyperheuristic component. The hyper-heuristic formed by combining a random heuristic selection with late acceptance strategy improves on the best results obtained in a previous study.