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On the Provision of Services With UAVs in Disaster Scenarios: A Two-Stage Stochastic Approach

Author

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  • Gabriella Colajanni

    (University of Catania)

  • Patrizia Daniele

    (University of Catania)

  • Daniele Sciacca

    (University of Catania)

Abstract

In this paper, we propose a two-stage stochastic optimization model for the provision services in a multi-tiered network, consisting in user or devices on the ground requiring services to controller UAVs in flight. The requested services are executed by a fleet of pre-existing and additional UAVs. The possible occurrence of disaster scenarios and the related uncertainty and severity could cause an unexpected and sudden increase in demand. Hence, the aim of the proposed model is to optimize the management of the pre-existing and additional resources in order to maximize the total profit of service providers and, simultaneously, minimize the expected loss related to a possible unmet demand. A variational approach is proposed, and some numerical examples are performed to validate the effectiveness of our model.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:snopef:v:3:y:2022:i:1:d:10.1007_s43069-022-00127-x
    DOI: 10.1007/s43069-022-00127-x
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    References listed on IDEAS

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    1. 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).
    2. Nagurney, Anna & Salarpour, Mojtaba & Daniele, Patrizia, 2019. "An integrated financial and logistical game theory model for humanitarian organizations with purchasing costs, multiple freight service providers, and budget, capacity, and demand constraints," International Journal of Production Economics, Elsevier, vol. 212(C), pages 212-226.
    3. 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).
    4. Caruso, Valeria & Daniele, Patrizia, 2018. "A network model for minimizing the total organ transplant costs," European Journal of Operational Research, Elsevier, vol. 266(2), pages 652-662.
    5. Anna Nagurney & Mojtaba Salarpour & June Dong & Ladimer S. Nagurney, 2020. "A Stochastic Disaster Relief Game Theory Network Model," SN Operations Research Forum, Springer, vol. 1(2), pages 1-33, June.
    6. Patrizia Daniele & Antonino Maugeri & Anna Nagurney, 2017. "Cybersecurity Investments with Nonlinear Budget Constraints: Analysis of the Marginal Expected Utilities," Springer Optimization and Its Applications, in: Nicholas J. Daras & Themistocles M. Rassias (ed.), Operations Research, Engineering, and Cyber Security, pages 117-134, Springer.
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    Cited by:

    1. Colajanni, Gabriella & Daniele, Patrizia & Sciacca, Daniele, 2022. "Reagents and swab tests during the COVID-19 Pandemic: An optimized supply chain management with UAVs," Operations Research Perspectives, Elsevier, vol. 9(C).
    2. 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.

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