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Detecting Promising Areas by Evolutionary Clustering Search

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Advances in Artificial Intelligence – SBIA 2004 (SBIA 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3171))

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Abstract

A challenge in hybrid evolutionary algorithms is to define efficient strategies to cover all search space, applying local search only in actually promising search areas. This paper proposes a way of detecting promising search areas based on clustering. In this approach, an iterative clustering works simultaneously to an evolutionary algorithm accounting the activity (selections or updatings) in search areas and identifying which of them deserves a special interest. The search strategy becomes more aggressive in such detected areas by applying local search. A first application to unconstrained numerical optimization is developed, showing the competitiveness of the method.

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Author information

Authors and Affiliations

  1. Departamento de Informática, Universidade Federal do Maranhão – UFMA, S. Luís, MA, Brasil

    Alexandre C. M. Oliveira

  2. Instituto Nacional de Pesquisas Espaciais – INPE, Laboratório Associado de Computação e Matemática Aplicada, S. José dos Campos, SP, Brasil

    Alexandre C. M. Oliveira & Luiz A. N. Lorena

Authors
  1. Alexandre C. M. Oliveira
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  2. Luiz A. N. Lorena
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Editor information

Editors and Affiliations

  1. Instituto de Informática, UFRGS, Porto Alegre, RS, Brasil

    Ana L. C. Bazzan

  2. Intelligent Systems Laboratory LSI, Center of Technology, Federal University of Maranao UFMA, Bacanga Campus, 65080-040, Sao Luis, MA, Brazil

    Sofiane Labidi

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© 2004 Springer-Verlag Berlin Heidelberg

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Oliveira, A.C.M., Lorena, L.A.N. (2004). Detecting Promising Areas by Evolutionary Clustering Search. In: Bazzan, A.L.C., Labidi, S. (eds) Advances in Artificial Intelligence – SBIA 2004. SBIA 2004. Lecture Notes in Computer Science(), vol 3171. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28645-5_39

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  • DOI: https://doi.org/10.1007/978-3-540-28645-5_39

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23237-7

  • Online ISBN: 978-3-540-28645-5

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