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<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, simulated annealing, genetic algorithms and memetic algorithms.
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