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Glider Routing and Trajectory Optimisation in disaster assessment

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  • Pereira Coutinho, Walton
  • Fliege, Jörg
  • Battarra, Maria

Abstract

In this paper, we introduce the Glider Routing and Trajectory Optimisation Problem (GRTOP), the problem of simultaneously finding optimal routes and trajectories for a fleet of gliders with the aim of surveying a set of locations. We propose a novel Mixed-Integer Nonlinear Programming (MINLP) formulation for the GRTOP, which optimises the routes as well as the trajectories along these routes, while flight dynamics is modelled as constraints. We avoid solving a non-convex problem by linearising the gliders’ flight dynamics, converting the proposed MINLP into a Mixed-Integer Second-order Cone Programming (MISOCP) problem. To allow for a more tractable formulation, the dynamical constraints are relaxed and a penalisation is added to the objective function. Several different discretisation techniques are compared. The formulation is tested on instances inspired by risk maps of flooding-prone cities across the UK and on 180 randomly generated instances.

Suggested Citation

  • Pereira Coutinho, Walton & Fliege, Jörg & Battarra, Maria, 2019. "Glider Routing and Trajectory Optimisation in disaster assessment," European Journal of Operational Research, Elsevier, vol. 274(3), pages 1138-1154.
    • Handle: RePEc:eee:ejores:v:274:y:2019:i:3:p:1138-1154
    DOI: 10.1016/j.ejor.2018.10.057
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    References listed on IDEAS

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    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. P. Matl & R. F. Hartl & T. Vidal, 2018. "Workload Equity in Vehicle Routing Problems: A Survey and Analysis," Transportation Science, INFORMS, vol. 52(2), pages 239-260, March.
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    Cited by:

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    2. Qinxiao Yu & Yossiri Adulyasak & Louis-Martin Rousseau & Ning Zhu & Shoufeng Ma, 2022. "Team Orienteering with Time-Varying Profit," INFORMS Journal on Computing, INFORMS, vol. 34(1), pages 262-280, January.
    3. Zhang, Guowei & Zhu, Ning & Ma, Shoufeng & Xia, Jun, 2021. "Humanitarian relief network assessment using collaborative truck-and-drone system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    4. 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.
    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. Duygu Pamukcu & Burcu Balcik, 2020. "A multi-cover routing problem for planning rapid needs assessment under different information-sharing settings," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 42(1), pages 1-42, March.
    7. Lorena Reyes-Rubiano & Jana Voegl & Klaus-Dieter Rest & Javier Faulin & Patrick Hirsch, 2021. "Exploration of a disrupted road network after a disaster with an online routing algorithm," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(1), pages 289-326, March.

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