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Using tornado-related weather data to route unmanned aerial vehicles to locate damage and victims

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  • Sean Grogan

    (Polytechnique Montréal)

  • Robert Pellerin

    (Polytechnique Montréal)

  • Michel Gamache

    (Polytechnique Montréal)

Abstract

This paper presents a framework for the use of unmanned aerial vehicles (UAVs) equipped with cameras and wireless sensors to search an area after the occurrence of a tornado. This paper attempts to demonstrate how tornado weather data can be incorporated into search and rescue procedures to allocate and route the UAVs. Traditionally, the time to assess and search an area after a tornado strikes is on the order of several days. Incorporating UAVs into a search and rescue team’s available tools can reduce this time span to the order of hours. These methods are applied and model in this project to three real-world cases. Several methods for creating ”waypoints,” points of interest for the UAVs to inspect, to route the UAVs were tested. An analysis was performed to compare the time it took to generate the waypoints and the resulting objective function value. It is observed that while there is an opportunity to use exact methods to generate waypoints, our proposed heuristic is sufficient for the rapid response needed in post-disaster relief.

Suggested Citation

  • 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.
  • Handle: RePEc:spr:orspec:v:43:y:2021:i:4:d:10.1007_s00291-021-00640-1
    DOI: 10.1007/s00291-021-00640-1
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    References listed on IDEAS

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    1. 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.
    2. Walton Pereira Coutinho & Roberto Quirino do Nascimento & Artur Alves Pessoa & Anand Subramanian, 2016. "A Branch-and-Bound Algorithm for the Close-Enough Traveling Salesman Problem," INFORMS Journal on Computing, INFORMS, vol. 28(4), pages 752-765, November.
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    Cited by:

    1. Maria Elena Bruni & Sara Khodaparasti, 2022. "A Variable Neighborhood Descent Matheuristic for the Drone Routing Problem with Beehives Sharing," Sustainability, MDPI, vol. 14(16), pages 1-14, August.

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