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An edge-based stochastic facility location problem in UAV-supported humanitarian relief logistics: a case study of Tehran earthquake

Author

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  • Mahmoud Golabi

    (Eastern Mediterranean University)

  • Seyed Mahdi Shavarani

    (Eastern Mediterranean University)

  • Gokhan Izbirak

    (Eastern Mediterranean University)

Abstract

The application of facility location problems in choosing the best location of relief distribution centers plays a salient role in emergency operations of large-scale disasters. On the premise that the service recipients are uniformly distributed along the network edges, this study investigates a combined mobile and immobile pre-earthquake facility location problem. A predefined number of locations are to be selected among a set of potential locations. Each facility is used in the relief distribution operation. It is incontrovertible that due to earthquakes, some network edges collapse and corresponding areas may lose their accessibility. Thus in this study, it is assumed that people on intact and accessible edges travel to the location of the distribution centers to receive the relief. For those who are located on collapsed or inaccessible network edges, the medium-scale unmanned aerial vehicle (UAV) helicopters are utilized in the relief distribution operation. This study aims to develop a mathematical model which minimizes the aggregate traveling time for both people and UAVs over a set of feasible scenarios. Since the network problems are NP-hard, some metaheuristic algorithms are developed to solve the proposed model. In order to demonstrate the applicability of developed model, a case study based on feasible earthquake scenarios in Tehran is presented.

Suggested Citation

  • Mahmoud Golabi & Seyed Mahdi Shavarani & Gokhan Izbirak, 2017. "An edge-based stochastic facility location problem in UAV-supported humanitarian relief logistics: a case study of Tehran earthquake," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 87(3), pages 1545-1565, July.
    • Handle: RePEc:spr:nathaz:v:87:y:2017:i:3:d:10.1007_s11069-017-2832-4
    DOI: 10.1007/s11069-017-2832-4
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    3. Dukkanci, Okan & Koberstein, Achim & Kara, Bahar Y., 2023. "Drones for relief logistics under uncertainty after an earthquake," European Journal of Operational Research, Elsevier, vol. 310(1), pages 117-132.
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    5. Ghasemi, Peiman & Khalili-Damghani, Kaveh & Hafezalkotob, Ashkan & Raissi, Sadigh, 2019. "Uncertain multi-objective multi-commodity multi-period multi-vehicle location-allocation model for earthquake evacuation planning," Applied Mathematics and Computation, Elsevier, vol. 350(C), pages 105-132.
    6. Sean Grogan & Robert Pellerin & Michel Gamache, 2021. "Using tornado-related weather data to route unmanned aerial vehicles to locate damage and victims," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(4), pages 905-939, December.
    7. İbrahim Miraç Eligüzel & Eren Özceylan & Gerhard-Wilhelm Weber, 2023. "Location-allocation analysis of humanitarian distribution plans: a case of United Nations Humanitarian Response Depots," Annals of Operations Research, Springer, vol. 324(1), pages 825-854, May.
    8. Shiva Ilkhanizadeh & Mahmoud Golabi & Siamand Hesami & Husam Rjoub, 2020. "The Potential Use of Drones for Tourism in Crises: A Facility Location Analysis Perspective," JRFM, MDPI, vol. 13(10), pages 1-13, October.
    9. Dukkanci, Okan & Campbell, James F. & Kara, Bahar Y., 2024. "Facility location decisions for drone delivery: A literature review," European Journal of Operational Research, Elsevier, vol. 316(2), pages 397-418.
    10. Kunovjanek, Maximilian & Wankmüller, Christian, 2021. "Containing the COVID-19 pandemic with drones - Feasibility of a drone enabled back-up transport system," Transport Policy, Elsevier, vol. 106(C), pages 141-152.
    11. Tongxin Liu & Jun Li & Xihui Wang, 2024. "Enhancing the cost performance in regular humanitarian logistics: location-routing and delivery frequency optimization," Flexible Services and Manufacturing Journal, Springer, vol. 36(3), pages 1157-1185, September.
    12. Xinhui Ren & Ruibo Li, 2023. "The Location Problem of Medical Drone Vertiports for Emergency Cardiac Arrest Needs," Sustainability, MDPI, vol. 16(1), pages 1-22, December.
    13. Wang, Jianxin & Lim, Ming K. & Zhan, Yuanzhu & Wang, XiaoFeng, 2020. "An intelligent logistics service system for enhancing dispatching operations in an IoT environment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 135(C).
    14. Béla Vizvári & Mahmoud Golabi & Arman Nedjati & Ferhat Gümüşbuğa & Gokhan Izbirak, 2019. "Top-down approach to design the relief system in a metropolitan city using UAV technology, part I: the first 48 h," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 99(1), pages 571-597, October.
    15. İlknur Tükenmez & Tugba Saraç & Onur Kaya, 2024. "A MILP model and a heuristic algorithm for post-disaster connectivity problem with heterogeneous vehicles," Journal of Heuristics, Springer, vol. 30(5), pages 359-396, December.

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