Metaheuristic Optimization

Diego Oliva, Mohamed Abd Elaziz, Salvador Hinojosa

Research output: Chapter in Book/Report/Conference proceedingChapter

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 languageEnglish
Title of host publicationStudies in Computational Intelligence
PublisherSpringer Verlag
Pages13-26
Number of pages14
DOIs
Publication statusPublished - 2019
Externally publishedYes

Publication series

NameStudies in Computational Intelligence
Volume825
ISSN (Print)1860-949X

ASJC Scopus subject areas

  • Artificial Intelligence

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  • Cite this

    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