metaheuristic
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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, simulated annealing, genetic algorithms and memetic algorithms.
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.
This article is provided by FOLDOC - Free Online Dictionary of Computing (foldoc.org)