Y, computabilitY> A top-level general strategY which guides other heuristics to search for feasible solutions in domains where the task is hard. Metaheuristics have been most generallY applied to problems classified as NP-Hard or NP-Complete bY the theorY of computational complexitY. However, metaheuristics would also be applied to other combinatorialoptimisation problems for which it is known that a polYnomial-time solution exists but is not practical. Examples of metaheuristics are Tabu Search, {simulated annealing}, {genetic algorithms} and {memetic algorithms}. (1997-10-30)