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Metaheuristic Algorithms for Image Segmentation: Theory and Applications pp 13–26Cite as

Metaheuristic Optimization

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 825))

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.

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Author information

Authors and Affiliations

  1. Departamento de Electrónica, CUCEI, Universidad de Guadalajara, Guadalajara, Jalisco, Mexico

    Diego Oliva

  2. Faculty of Science, Zagazig University, Zagazig, Egypt

    Mohamed Abd Elaziz

  3. Facultad de Informática, Universidad Complutense de Madrid, Madrid, Spain

    Salvador Hinojosa

Authors
  1. Diego Oliva
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  2. Mohamed Abd Elaziz
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  3. Salvador Hinojosa
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Corresponding author

Correspondence to Diego Oliva .

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Oliva, D., Abd Elaziz, M., Hinojosa, S. (2019). Metaheuristic Optimization. In: Metaheuristic Algorithms for Image Segmentation: Theory and Applications. Studies in Computational Intelligence, vol 825. Springer, Cham. https://doi.org/10.1007/978-3-030-12931-6_3

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