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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. © 2009 IEEE. 2009 IEEE Congress on Evolutionary Computation, CEC 2009 -- 18 May 2009 through 21 May 2009 -- Trondheim -- 77108 Engineering and Physical Sciences Research Council: EP/D061571/1 Engineering and Physical Sciences Research Council: EP/F033214/1