Metaheuristic Optimization

Abstract

In the area of global optimization, a large number of Metaheuristic Algorithms (MA) had been proposed over the years to solve complex engineering problems in a reasonable amount of time. MAs are stochastic search algorithms that use rules or heuristics applicable to any problem to accelerate their convergence to near-optimal solutions. It is common to observe that MAs emulate processes and behaviors inspired by mechanisms present in nature, such as evolution. In this chapter, the most relevant topics of metaheuristic algorithms are discussed.

Original language	English
Title of host publication	Studies in Computational Intelligence
Publisher	Springer Verlag
Pages	13-26
Number of pages	14
DOIs	https://doi.org/10.1007/978-3-030-12931-6_3
Publication status	Published - 2019
Externally published	Yes

Publication series

Name	Studies in Computational Intelligence
Volume	825
ISSN (Print)	1860-949X

ASJC Scopus subject areas

Artificial Intelligence

Access to Document

10.1007/978-3-030-12931-6_3

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Oliva, D., Abd Elaziz, M., & Hinojosa, S. (2019). Metaheuristic Optimization. In Studies in Computational Intelligence (pp. 13-26). (Studies in Computational Intelligence; Vol. 825). Springer Verlag. https://doi.org/10.1007/978-3-030-12931-6_3

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