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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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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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Correspondence to Sami Mnasri .

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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

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  • Online ISBN: 978-3-319-67910-5

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