A metaheuristic is a set of concepts that can be used to define heuristic methods that can be applied to a wide set of different problems. In other words, a metaheuristic can be seen as a general algorithmic framework that can be applied to different optimization problems with relatively few modifications. Examples of metaheuristics include simulated annealing, tabu search, iterated local search, evolutionary algorithms, and ant colony optimization.
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Dorigo, M., Birattari, M., Stützle, T. (2017). Metaheuristic. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning and Data Mining. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7687-1_537
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DOI: https://doi.org/10.1007/978-1-4899-7687-1_537
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