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Charging Stations Distribution Optimization using Drones Fleet for Disaster Prone Areas

Author

Listed:
  • Zohaib Hassan

    (Electrical and Computer Engineering Department, Air University, Islamabad, Pakistan)

  • Irtiza Ali Shah

    (Department of Mechanical and Aerospace Engineering, AirUniversity, Islamabad, Pakistan)

  • Ahsan Sarwar Rana

    (Electrical and Computer Engineering Department, Air University, Islamabad, Pakistan)

Abstract

A disaster is an unforeseen calamity that causes damage to property or brings about a loss of human life. Quick response and rapid distribution of vital relief items into the affected region could save precious lives. In this regard, disaster management comes into play, which is highly dependent on the topography of the disaster-hit area. If the disaster-hit area has little or no road connectivity, the use of drones in such areas becomes essential for the delivery of health packages. Since the battery capacity of the drone is limited, there is a need of charging stations that should be transported using road infrastructure and pre-installed in disaster-prone areas, as access to these areas may be denied once the disaster hits. In this article, a simulation model was used to optimize the number and location of drone charging stations for deployment in a disaster-prone area in the pre-disaster scenario, aiming at the distribution of relief items to disaster-hit areas in the post-disaster scenario. We consider the relative priority of locations where a preference is given to the locations that have higher priority levels. An optimal number of charging stations and optimal routes have also been determined by using our optimization model. To illustrate the use of our model, numerical examples have been simulated for different sizes of the disaster-hit area and the number of targets. In our numerical simulation, it was observed that the drone's maximum distance capacity is the key factor in determining the optimal grid size, which directly correlates to the number of charging stations.

Suggested Citation

  • Zohaib Hassan & Irtiza Ali Shah & Ahsan Sarwar Rana, 2022. "Charging Stations Distribution Optimization using Drones Fleet for Disaster Prone Areas," International Journal of Innovations in Science & Technology, 50sea, vol. 4(5), pages 103-121, June.
  • Handle: RePEc:abq:ijist1:v:4:y:2022:i:5:p:103-121
    DOI: 10.33411/IJIST/2022040509
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    References listed on IDEAS

    as
    1. Chowdhury, Sudipta & Emelogu, Adindu & Marufuzzaman, Mohammad & Nurre, Sarah G. & Bian, Linkan, 2017. "Drones for disaster response and relief operations: A continuous approximation model," International Journal of Production Economics, Elsevier, vol. 188(C), pages 167-184.
    2. Jose Escribano Macias & Nils Goldbeck & Pei-Yuan Hsu & Panagiotis Angeloudis & Washington Ochieng, 2020. "Endogenous stochastic optimisation for relief distribution assisted with unmanned aerial vehicles," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 42(4), pages 1089-1125, December.
    3. Baskaya, Serhat & Ertem, Mustafa Alp & Duran, Serhan, 2017. "Pre-positioning of relief items in humanitarian logistics considering lateral transhipment opportunities," Socio-Economic Planning Sciences, Elsevier, vol. 57(C), pages 50-60.
    4. Hu, Shaolong & Han, Chuanfeng & Dong, Zhijie Sasha & Meng, Lingpeng, 2019. "A multi-stage stochastic programming model for relief distribution considering the state of road network," Transportation Research Part B: Methodological, Elsevier, vol. 123(C), pages 64-87.
    5. Ferrer, José M. & Martín-Campo, F. Javier & Ortuño, M. Teresa & Pedraza-Martínez, Alfonso J. & Tirado, Gregorio & Vitoriano, Begoña, 2018. "Multi-criteria optimization for last mile distribution of disaster relief aid: Test cases and applications," European Journal of Operational Research, Elsevier, vol. 269(2), pages 501-515.
    6. Armin Jabbarzadeh & Behnam Fahimnia & Fatemeh Sabouhi, 2018. "Resilient and sustainable supply chain design: sustainability analysis under disruption risks," International Journal of Production Research, Taylor & Francis Journals, vol. 56(17), pages 5945-5968, September.
    7. Rivera-Royero, Daniel & Galindo, Gina & Yie-Pinedo, Ruben, 2020. "Planning the delivery of relief supplies upon the occurrence of a natural disaster while considering the assembly process of the relief kits," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).
    8. Huma Ahmed Hassan & Syed Amer Mahmood, 2020. "Generation of Digital Surface Model (DSM) USING UAV/ QUADCOPTER," International Journal of Innovations in Science & Technology, 50sea, vol. 2(3), pages 89-107, September.
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    More about this item

    Keywords

    Drone Charging Stations; Prepadness and Response; Drone Path Planning; Energy Optimization; Drone Recharging;
    All these keywords.

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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