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Mission Planning for Emergency Rapid Mapping with Drones

Author

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  • Katharina Glock

    (FZI Research Center for Information Technology, 76131 Karlsruhe, Germany)

  • Anne Meyer

    (TU Dortmund University, 44227 Dortmund, Germany)

Abstract

We introduce a mission planning concept for routing unmanned aerial vehicles (UAVs) through a set of sampling locations in the immediate aftermath of an incident such as a fire or chemical accident. Using interpolation methods that account for the spatial interdependencies inherent in the surveyed phenomenon, these samples allow predicting the distribution of hazardous substances across the affected area. We define the generalized correlated team orienteering problem (GCorTOP) for selecting informative samples considering spatial correlations between observed and unobserved locations, as well as priorities in the surveyed area. To quickly provide high-quality solutions in time-sensitive situations, we propose a two-phase multistart adaptive large neighborhood search (2MLS). We show the competitiveness of the solution approach using benchmark instances for the team orienteering problem and investigate the performance of the proposed models and solution approach in an extensive study based on newly introduced benchmark instances for the mission planning problem.

Suggested Citation

  • Katharina Glock & Anne Meyer, 2020. "Mission Planning for Emergency Rapid Mapping with Drones," Transportation Science, INFORMS, vol. 54(2), pages 534-560, March.
    • Handle: RePEc:inm:ortrsc:v:54:y:2020:i:2:p:534-560
    DOI: 10.1287/trsc.2019.0963
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Johannes Schmidt & Armin Fügenschuh, 2023. "A two-time-level model for mission and flight planning of an inhomogeneous fleet of unmanned aerial vehicles," Computational Optimization and Applications, Springer, vol. 85(1), pages 293-335, May.
    2. Meyer, Anne & Glock, Katharina & Radaschewski, Frank, 2021. "Planning profitable tours for field sales forces: A unified view on sales analytics and mathematical optimization," Omega, Elsevier, vol. 105(C).
    3. Fang, Chao & Han, Zonglei & Wang, Wei & Zio, Enrico, 2023. "Routing UAVs in landslides Monitoring: A neural network heuristic for team orienteering with mandatory visits," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).
    4. Glock, Katharina & Meyer, Anne, 2023. "Spatial coverage in routing and path planning problems," European Journal of Operational Research, Elsevier, vol. 305(1), pages 1-20.
    5. Zhang, Guowei & Jia, Ning & Zhu, Ning & Adulyasak, Yossiri & Ma, Shoufeng, 2023. "Robust drone selective routing in humanitarian transportation network assessment," European Journal of Operational Research, Elsevier, vol. 305(1), pages 400-428.
    6. Mohammadmehdi Hakimifar & Burcu Balcik & Christian Fikar & Vera Hemmelmayr & Tina Wakolbinger, 2022. "Evaluation of field visit planning heuristics during rapid needs assessment in an uncertain post-disaster environment," Annals of Operations Research, Springer, vol. 319(1), pages 517-558, December.

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