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Hybrid Whale Optimization Algorithm with Simulated Annealing for the UAV Placement Problem

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Future Research Directions in Computational Intelligence (CICom 2022)

Part of the book series: EAI/Springer Innovations in Communication and Computing ((EAISICC))

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Abstract

This chapter suggests a hybrid algorithm based on the combination of whale optimization algorithm (WOA) with simulated annealing (SA), called WOA-SA, for solving the unmanned aerial vehicle (UAV) placement problem. WOA-SA combines WOA’s global search functionality with SA’s local search functionality. The main objective of our work is to determine the optimal position of the UAV in order to maximize the total throughput, depending on a given set of user locations and traffic demands. The WOA-SA algorithm is validated in terms of the total throughput using 18 distinct instances with various numbers of users, taking into account the effect of the distribution of user positions. The results of simulation using Matlab demonstrated that the WOA-SA algorithm obtains better results than WOA, SA, Particle Swam Optimization (PSO), Genetic Algorithm (GA), and Bat Algorithm (BA).

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Author information

Authors and Affiliations

  1. LIST Laboratory, University of M’Hamed Bougara Boumerdes, Boumerdes, Algeria

    Sylia Mekhmoukh Taleb, Yassine Meraihi & Selma Yahia

  2. LISV Laboratory, University of Versailles St-Quentin-en-Yvelines, Velizy, France

    Amar Ramdane-Cherif

  3. Laboratoire LMCS, Ecole Nationale Supérieure d’Informatique, Oued Smar, Alger, Algeria

    Asma Benmessaoud Gabis

  4. LAA Laboratory, University of M’Hamed Bougara Boumerdes, Boumerdes, Algeria

    Dalila Acheli

Authors
  1. Sylia Mekhmoukh Taleb
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  2. Yassine Meraihi
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  3. Selma Yahia
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  4. Amar Ramdane-Cherif
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  5. Asma Benmessaoud Gabis
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  6. Dalila Acheli
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Corresponding author

Correspondence to Sylia Mekhmoukh Taleb .

Editor information

Editors and Affiliations

  1. ECE Research Center, Omnes Education, ECE Engineering School, Paris, France

    Manolo Dulva Hina

  2. Centre for AI Research and Optimisation, Torrens University Australia, Brisbane, QLD, Australia

    Seyedali Mirjalili

  3. LISV laboratory, University of Versailles - Paris-Saclay, Vélizy, France

    Amar Ramdane-Cherif

  4. ICS - 5G & 6G Innovation Centre, University of Surrey, Guildford, Surrey, UK

    Rafik Zitouni

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© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Taleb, S.M., Meraihi, Y., Yahia, S., Ramdane-Cherif, A., Gabis, A.B., Acheli, D. (2024). Hybrid Whale Optimization Algorithm with Simulated Annealing for the UAV Placement Problem. In: Hina, M.D., Mirjalili, S., Ramdane-Cherif, A., Zitouni, R. (eds) Future Research Directions in Computational Intelligence. CICom 2022. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-031-34459-6_6

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  • DOI: https://doi.org/10.1007/978-3-031-34459-6_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-34458-9

  • Online ISBN: 978-3-031-34459-6

  • eBook Packages: EngineeringEngineering (R0)

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