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A Hybrid Ant-Genetic Algorithm to Solve a Real Deployment Problem: A Case Study with Experimental Validation

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Ad-hoc, Mobile, and Wireless Networks (ADHOC-NOW 2017)

Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 10517))

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Abstract

In this paper, we investigate the problem of deploying 3D nodes in a wireless sensor network. The aim is to choose the ideal 3D locations to add new nodes to an initial configuration of nodes, while optimizing a set of objectives. In this regard, our study proposes a new hybrid algorithm which stems from the ant foraging behavior and the genetics. It is based on a recent variant of the genetic algorithms (NSGA-III) and the Ant Colony Optimization algorithm. The obtained numerical results and the simulations compared with experiments prove the effectiveness of the proposed approach.

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Authors and Affiliations

  1. University of Toulouse, UT2J, CNRS-IRIT-IRT, Toulouse, France

    Sami Mnasri, Adrien Van Den Bossche & Thierry Val

  2. ENIS, LETI, University of Sfax, Sfax, Tunisia

    Nejah Nasri

Authors
  1. Sami Mnasri
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  2. Nejah Nasri
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  3. Adrien Van Den Bossche
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  4. Thierry Val
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Corresponding author

Correspondence to Sami Mnasri .

Editor information

Editors and Affiliations

  1. University of Messina, Messina, Italy

    Antonio Puliafito

  2. University of Messina, Messina, Italy

    Dario Bruneo

  3. University of Messina, Messina, Italy

    Salvatore Distefano

  4. Kazan Federal University, Kazan, Russia

    Francesco Longo

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Mnasri, S., Nasri, N., Van Den Bossche, A., Val, T. (2017). A Hybrid Ant-Genetic Algorithm to Solve a Real Deployment Problem: A Case Study with Experimental Validation. In: Puliafito, A., Bruneo, D., Distefano, S., Longo, F. (eds) Ad-hoc, Mobile, and Wireless Networks. ADHOC-NOW 2017. Lecture Notes in Computer Science(), vol 10517. Springer, Cham. https://doi.org/10.1007/978-3-319-67910-5_30

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  • DOI: https://doi.org/10.1007/978-3-319-67910-5_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67909-9

  • Online ISBN: 978-3-319-67910-5

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