A Tabu-Search Hyperheuristic for Timetabling and Rostering
Journal of Heuristics
Choosing the fittest subset of low level heuristics in a hyperheuristic framework
EvoCOP'05 Proceedings of the 5th European conference on Evolutionary Computation in Combinatorial Optimization
One hyper-heuristic approach to two timetabling problems in health care
Journal of Heuristics
An intelligent hyper-heuristic framework for CHeSC 2011
LION'12 Proceedings of the 6th international conference on Learning and Intelligent Optimization
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The present study investigates the effect of heuristic sets on the performance of several selection hyper-heuristics. The performance of selection hyper-heuristics is strongly dependant on low-level heuristic sets employed for solving target problems. Therefore, the generality of hyper-heuristics should be examined across various heuristic sets. Unlike the majority of hyper-heuristics research, where the low-level heuristic set is considered given, the present study investigates the influence of the low-level heuristics on the hyper-heuristic's performance. To achieve this, a number of heuristic sets was generated for the patient admission scheduling problem by setting the parameters of a set of parametric heuristics with specific values. These values were set such that nine heuristic sets with different improvement capabilities, speed characteristics and size were generated. A group of hyper-heuristics with certain selection mechanisms and acceptance criteria having dissimilar intensification/diversification abilities were taken from the literature enabling a comprehensive analysis. The experimental results indicated that different hyper-heuristics perform superiorly on distinct heuristic sets. The results can be explained and hence result in hyper-heuristic design recommendations.