Author:

Keywords:

hyper-heuristics, CHeSC, learning, itec

Abstract:

The present study proposes a new selection hyper-heuristic providing several adaptive features to cope with the requirements of managing different heuristic sets. The approach suggested provides an intelligent way of selecting heuristics, determines effective heuristic pairs and adapts the parameters of certain heuristics online. In addition, an adaptive list-based threshold accepting mechanism has been developed. It enables deciding whether to accept or not the solutions generated by the selected heuristics. The resulting approach won the first Cross Domain Heuristic Search Challenge against 19 high-level algorithms. The detailed empirical results concerning the behaviour of the hyper-heuristic and its sub-mechanisms will be presented at the conference.