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Advances in Nature and Biologically Inspired Computing pp 189–199Cite as

Bioinspired Tabu Search for Geographic Partitioning

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 419))

Abstract

The analytical observation of nature induces inspiration to propose new computational paradigms to create algorithms that solve optimization and artificial intelligence problems. The artificial vision allows establishing a problem with intelligent techniques from living systems. The bioinspired systems are presented as a set of models that are based on the behavior and the way of acting of some biological systems. These models can be expressed in data mining and operations research where the clustering is a recurrent technique in the P-median problem and territorial design. On this point, we have solved clustering problems using partitioning with bioinspired aspects and variable neighborhood search to approximate optimal solutions. In this work we have improved the search strategy: we present a bioinspired partitioning algorithm with optimization by tabu search (TS). This clustering problem under a bioinspired connotation has been proposed after observing some characteristics in common between clustering and human behavior in conflict situations, where some characteristics have been modeled.

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Authors and Affiliations

  1. Facultad de Ciencias de la Computación, Benemérita Universidad Autónoma de Puebla, Puebla, Mexico

    María Beatríz Bernábe-Loranca, Rogelio González Velazquez, Martín Estrada Analco & Abraham Sánchez

  2. Universidad Autónoma del Estado de Hidalgo, Pachuca, Mexico

    Jorge Ruíz-Vanoye & Alejandro Fuentes Penna

Authors
  1. María Beatríz Bernábe-Loranca
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  2. Rogelio González Velazquez
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  3. Martín Estrada Analco
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  4. Jorge Ruíz-Vanoye
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  5. Alejandro Fuentes Penna
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  6. Abraham Sánchez
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Corresponding author

Correspondence to María Beatríz Bernábe-Loranca .

Editor information

Editors and Affiliations

  1. School of Mathematics, Statistics and CS, University of KwaZulu-Natal, Pietermaritzburg, South Africa

    Nelishia Pillay

  2. Sch of IT, Dept of CS, University of Pretoria, Pretoria, South Africa

    Andries P. Engelbrecht

  3. Sci N/w for Innova and Research Exc, Machine Intelligence Research Labs, Auburn, Washington, USA

    Ajith Abraham

  4. Department of Computing Sciences,, Nelson Mandela Metropolitan University, Port Elizabeth, South Africa

    Mathys C. du Plessis

  5. Faculty of Electrical Engineering and, Technical University of Ostrava, Ostrava-Poruba, Czech Republic

    Václav Snášel

  6. Fakulti Teknologi Maklumat dan Komunikas, Universiti Teknikal Malaysia Melaka, Durian Tunggal, Malaysia

    Azah Kamilah Muda

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Bernábe-Loranca, M.B., Velazquez, R.G., Analco, M.E., Ruíz-Vanoye, J., Penna, A.F., Sánchez, A. (2016). Bioinspired Tabu Search for Geographic Partitioning. In: Pillay, N., Engelbrecht, A., Abraham, A., du Plessis, M., Snášel, V., Muda, A. (eds) Advances in Nature and Biologically Inspired Computing. Advances in Intelligent Systems and Computing, vol 419. Springer, Cham. https://doi.org/10.1007/978-3-319-27400-3_17

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  • DOI: https://doi.org/10.1007/978-3-319-27400-3_17

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27399-0

  • Online ISBN: 978-3-319-27400-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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