Supervisor: Dr John Drake
Research group(s): Game AI, Operational Research
Optimisation problems often explore a search space which is too large to enumerate and exhaustively search for an optimal solution. Various heuristics and metaheuristics have been applied successfully to problems of this nature. One drawback of such approaches is the necessity to manually adapt the method used to solve different problem domains or classes of problem. Hyper-heuristics are a class of high-level search techniques which aim to raise the level of generality at which search methods operate. Unlike traditional techniques, a hyper-heuristic operates on a search space of heuristics rather than directly on the search space of solutions.
The last decade or so has seen sustained research effort directed at hyper-heuristic methods, much of which is a result of pioneering work done by researchers within the OR Group at QMUL. This project will apply hyper-heuristic methods to well-known real-world combinatorial optimisation problems, seeking to automate the heuristic design process, reducing the time required to develop such methods and the burden on the human involved in the development cycle.