Meta-heuristics is the most recent development in approximate search methods for solving complex optimization problems that arise in business, commerce, engineering, industry, and many other areas. A meta-heuristic guides a subordinate heuristic using concepts derived from artificial intelligence, biological, mathematical, natural, and physical sciences to improve their performance. Notable examples of meta-heuristics include genetic/evolutionary algorithms, Tabu search, simulated annealing, variable neighborhood search, GRASP, and ant colony optimization, among many others (see Meta-heuristics: theory and applications, I. H. Osman and J. P Kelly ed. Kluwer Academic Publishers, 1996).
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Ortuño, M.T. (2013). Meta-heuristics. In: Runehov, A.L.C., Oviedo, L. (eds) Encyclopedia of Sciences and Religions. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-8265-8_200871
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DOI: https://doi.org/10.1007/978-1-4020-8265-8_200871
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