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A three-stage stochastic optimization model integrating 5G technology and UAVs for disaster management

Author

Listed:
  • Gabriella Colajanni

    (University of Catania)

  • Patrizia Daniele

    (University of Catania)

  • Anna Nagurney

    (University of Massachusetts)

  • Ladimer S. Nagurney

    (University of Hartford)

  • Daniele Sciacca

    (University of Catania)

Abstract

In this paper, we develop a three-stage stochastic network-based optimization model for the provision of 5G services with Unmanned Aerial Vehicles (UAVs) in the disaster management phases of: preparedness, response and recover/reconstruction. Users or devices on the ground request services of a fleet of controller UAVs in flight and the requested services are executed by a fleet of UAVs organized as a Flying Ad-Hoc Network and interconnected via 5G technology. A disaster scenario can create difficulties for the provision of services by service providers. For this reason, in the first stage, service providers make predictions about possible scenarios in the second stage. Therefore, the first stage represents the preparedness phase, the second stage represents the response phase, followed by the recovery/reconstruction phase, represented by the third stage. In each of the three stages, service providers seek to maximize the amount of services to be performed, assigning each service a priority. They also aim to, simultaneously, minimize the total management costs of requests, the transmission and execution costs of services, the costs to increase the resources of the pre-existing network and, if need be, to reduce them in the recovery/reconstruction phase. For the proposed multi-stage stochastic optimization model, we provide variational formulations for which we investigate the existence and uniqueness of the solution. Finally, a detailed numerical example is solved in order underline some of the key aspects of the model. This paper adds to the literature on the rigorous mathematical modeling of advanced technologies for disaster management.

Suggested Citation

  • Gabriella Colajanni & Patrizia Daniele & Anna Nagurney & Ladimer S. Nagurney & Daniele Sciacca, 2023. "A three-stage stochastic optimization model integrating 5G technology and UAVs for disaster management," Journal of Global Optimization, Springer, vol. 86(3), pages 741-780, July.
  • Handle: RePEc:spr:jglopt:v:86:y:2023:i:3:d:10.1007_s10898-023-01274-z
    DOI: 10.1007/s10898-023-01274-z
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    References listed on IDEAS

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    1. Jinxia Cen & Tahar Haddad & Van Thien Nguyen & Shengda Zeng, 2022. "Simultaneous distributed-boundary optimal control problems driven by nonlinear complementarity systems," Journal of Global Optimization, Springer, vol. 84(3), pages 783-805, November.
    2. Nguyen, Minh Anh & Dang, Giang Thi-Huong & Hà, Minh Hoàng & Pham, Minh-Trien, 2022. "The min-cost parallel drone scheduling vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 299(3), pages 910-930.
    3. Anna Nagurney, 2022. "Labor and Supply Chain Networks," Springer Optimization and Its Applications, Springer, number 978-3-031-20855-3, June.
    4. Salarpour, Mojtaba & Nagurney, Anna, 2021. "A multicountry, multicommodity stochastic game theory network model of competition for medical supplies inspired by the Covid-19 pandemic," International Journal of Production Economics, Elsevier, vol. 236(C).
    5. Zheng, Fengjiao & Khan, Naseer Abbas & Hussain, Sabir, 2020. "The COVID 19 pandemic and digital higher education: Exploring the impact of proactive personality on social capital through internet self-efficacy and online interaction quality," Children and Youth Services Review, Elsevier, vol. 119(C).
    6. Li, Hongqi & Chen, Jun & Wang, Feilong & Bai, Ming, 2021. "Ground-vehicle and unmanned-aerial-vehicle routing problems from two-echelon scheme perspective: A review," European Journal of Operational Research, Elsevier, vol. 294(3), pages 1078-1095.
    7. G Barbarosoǧlu & Y Arda, 2004. "A two-stage stochastic programming framework for transportation planning in disaster response," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(1), pages 43-53, January.
    8. Anna Nagurney, 2022. "Supply chain networks, wages, and labor productivity: insights from Lagrange. analysis and computations," Journal of Global Optimization, Springer, vol. 83(3), pages 615-638, July.
    9. Rennemo, Sigrid Johansen & Rø, Kristina Fougner & Hvattum, Lars Magnus & Tirado, Gregorio, 2014. "A three-stage stochastic facility routing model for disaster response planning," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 62(C), pages 116-135.
    10. Puerto, Justo & Valverde, Carlos, 2022. "Routing for unmanned aerial vehicles: Touring dimensional sets," European Journal of Operational Research, Elsevier, vol. 298(1), pages 118-136.
    11. Oleg Burdakov & Patrick Doherty & Kaj Holmberg & Per-Magnus Olsson, 2010. "Optimal placement of UV-based communications relay nodes," Journal of Global Optimization, Springer, vol. 48(4), pages 511-531, December.
    12. Tingting Cai & Dongmin Yu & Huanan Liu & Fengkai Gao, 2022. "RETRACTED: Computational Analysis of Variational Inequalities Using Mean Extra-Gradient Approach," Mathematics, MDPI, vol. 10(13), pages 1-14, July.
    13. Muhammad Aslam Noor & Khalida Inayat Noor & Eisa Al-Said, 2012. "On New Proximal Point Methods for Solving the Variational Inequalities," Journal of Applied Mathematics, Hindawi, vol. 2012, pages 1-7, November.
    14. Gabriella Colajanni & Patrizia Daniele & Daniele Sciacca, 2022. "On the Provision of Services With UAVs in Disaster Scenarios: A Two-Stage Stochastic Approach," SN Operations Research Forum, Springer, vol. 3(1), pages 1-30, March.
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