Perturbation based variable neighbourhood search in heuristic space for examination timetabling problem

Efficient constructive heuristics have been designed for most of the difficult combinatorial optimisation problems. Performance of these heuristics may vary from one instance to another and hence it is beneficial to be able to select an instance of the heuristic which is best suited to a given instance of the problem. Both of the heuristic search algorithm and hyper-heuristic approaches try to provide methodologies for selecting a heuristic from a set of given heuristics. In this paper we propose a perturbation based algorithm to search an infinite space of parameterised heuristics. This algorithm aims to find the best heuristic in a set of given heuristics and hence its success or failure are measured in terms of the quality of the solution generated by the selected heuristic compared to the other heuristics in the heuristic space. This approach was applied to a highly constrained instance of examination timetabling problem. Computational results show the ability of the perturbation based algorithm in finding good combinations of heuristics and their parameters with reasonable computational effort.