metaheuristic

algorithm, complexity, 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 combinatorial optimisation

problems for which it is known that a polynomial-time

solution exists but is not practical.

Examples of metaheuristics are Tabu Search, simulatedannealing, genetic algorithms and memetic algorithms.

(1997-10-30)