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Applying Bio-inspired Techniques to the p-Median Problem

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Computational Intelligence and Bioinspired Systems (IWANN 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3512))

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Abstract

Neural networks (NNs) and genetic algorithms (GAs) are the two most popular bio-inspired techniques. Criticism of these approaches includes the tendency of recurrent neural networks to produce infeasible solutions, the lack of generalize of the self-organizing approaches, and the requirement of tuning many internal parameters and operators of genetic algorithms. This paper proposes a new technique which enables feasible solutions, removes the tuning phase, and improves solutions quality of typical combinatorial optimization problems as the p-median problem. Moreover, several biology inspired approaches are analyzed for solving traditional benchmarks.

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Author information

Authors and Affiliations

  1. Department of Computer Science, E.T.S.I.Informatica, University of Malaga, Campus Teatinos s/n, 29071, Malaga, Spain

    E. Domínguez & J. Muñoz

Authors
  1. E. Domínguez
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  2. J. Muñoz
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Editor information

Editors and Affiliations

  1. Departamento de Ingeniería Electrónica, Universitat Politècnica de Catalunya (UPC). E.T.S.I. de Telecomunicación, Campus Norte, Edificio C4, C/ Jordi Girona, 1-3, E08034, Barcelona, Spain

    Joan Cabestany

  2. Department of Computer Architecture and Computer Technology, University of Granada,  

    Alberto Prieto

  3. Grupo ISIS, Dpto. Tecnología Electrónica ETSI Telecomunicación, Universidad de Málaga, Campus de Teatinos, 29071, Málaga, Spain

    Francisco Sandoval

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© 2005 Springer-Verlag Berlin Heidelberg

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Domínguez, E., Muñoz, J. (2005). Applying Bio-inspired Techniques to the p-Median Problem. In: Cabestany, J., Prieto, A., Sandoval, F. (eds) Computational Intelligence and Bioinspired Systems. IWANN 2005. Lecture Notes in Computer Science, vol 3512. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11494669_9

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  • DOI: https://doi.org/10.1007/11494669_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-26208-4

  • Online ISBN: 978-3-540-32106-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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