A hyper-heuristic algorithm involves a decision making process in which the heuristics to be used are selected from a set of alternatives.  This research aims at the development of a novel fuzzy inference methods to guide the selection process.  There are two main approaches which will be investigated: (a) fuzzy rule-based reasoning to determine a “good” set of rules to be used in the selection process, and (b) fuzzy similarity measures to be used in the comparison of potentially large number of previously performed search episodes.

Over the last twenty years or so, there has been significant scientific progress in building search methodologies and in tailoring those methodologies (usually through hybridisation with problem specific methods and information) for a very wide range of application areas. Such methodologies can be extremely effective in the hands of an expert but they require specialist human knowledge to be applied effectively in complex real world problem solving environments. The goal of developing automated systems to replace the human expert in this role is only just beginning to be seriously addressed by the scientific community, and the Automated Scheduling, Optimisation and Planning (ASAP) research group at Nottingham has played a pioneering role in placing this grand challenge upon the international scientific agenda. The aim of developing automated systems to intelligently select, evolve and develop search methods is an extremely ambitious and demanding research goal. The level of adventure should not be underestimated. The goal of exploring the boundaries between what is possible and what is not (with respect to the automation of the heuristic design process) represents one of the most important current research challenges to face the search and decision support community. Indeed, our aim is to build systems that can automatically create novel decision support software, thus substantially changing the research agenda and raising the level of generality and applicability of decision support systems.