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The Best Genetic Algorithm I

A Comparative Study of Structurally Different Genetic Algorithms

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Advances in Soft Computing and Its Applications (MICAI 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8266))

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Abstract

Genetic Algorithms (GAs) have long been recognized as powerful tools for optimization of complex problems where traditional techniques do not apply. However, although the convergence of elitist GAs to a global optimum has been mathematically proven, the number of iterations remains a case-by-case parameter. We address the problem of determining the best GA out of a family of structurally different evolutionary algorithms by solving a large set of unconstrained functions. We selected 4 structurally different genetic algorithms and a non-evolutionary one (NEA). A schemata analysis was conducted further supporting our claims. As the problems become more demanding, the GAs significantly and consistently outperform the NEA. A particular breed of GA (the Eclectic GA) is superior to all other, in all cases.

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Author information

Authors and Affiliations

  1. Instituto Tecnológico Autónomo de México, Río Hondo No. 1, México, 01000, D.F. México

    Angel Kuri-Morales

  2. IIMAS, Universidad Nacional Autónoma de México, México, 04510, D.F. México

    Edwin Aldana-Bobadilla

Authors
  1. Angel Kuri-Morales
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  2. Edwin Aldana-Bobadilla
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Editor information

Editors and Affiliations

  1. Universidad Autónoma del Estado de Hidalgo, Ciudad Universitaria, Carretera Pachuca–Tulancingo km 4.5, Hidalgo, Mexico

    Félix Castro

  2. Centro de Investigación en Computación, Instituto Politécnico Nacional, Av. Juan Dios Bátiz s/n, Col. Nueva Industrial Vallejo, 07738, Mexico City, Mexico

    Alexander Gelbukh

  3. Tecnológico de Monterrey, Campus Estado de México, Carretera Lago de Guadalupe Km 3.5, Atizapán de Zaragoza, 52926, Estado de México, CP, Mexico

    Miguel González

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Kuri-Morales, A., Aldana-Bobadilla, E. (2013). The Best Genetic Algorithm I. In: Castro, F., Gelbukh, A., González, M. (eds) Advances in Soft Computing and Its Applications. MICAI 2013. Lecture Notes in Computer Science(), vol 8266. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-45111-9_1

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  • DOI: https://doi.org/10.1007/978-3-642-45111-9_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-45110-2

  • Online ISBN: 978-3-642-45111-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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