Highlights A framework to model UAV-based humanitarian logistics missions is defined. A mixed integer programming formulation for the problem is presented. An effective Large Neighbourhood Search approach is proposed to solve this problem. The algorithm optimises trajectories, depot location and battery allocation.
Abstract Unmanned Aerial Vehicles (UAVs) are being increasingly deployed in humanitarian response operations. Beyond regulations, vehicle range and integration with the humanitarian supply chain inhibit their deployment. To address these issues, we present a novel bi-stage operational planning approach that consists of a trajectory optimisation algorithm (that considers multiple flight stages), and a hub selection-routing algorithm that incorporates a new battery management heuristic. We apply the algorithm to a hypothetical response mission in Taiwan after the Chi-Chi earthquake of 1999 considering mission duration and distribution fairness. Our analysis indicates that UAV fleets can be used to provide rapid relief to populations of 20,000 individuals in under 24 h. Additionally, the proposed methodology achieves significant reductions in mission duration and battery stock requirements with respect to conservative energy estimations and other heuristics.
Optimal hub selection for rapid medical deliveries using unmanned aerial vehicles
Tramsportation Research, Part C: Emerging Technologies ; 110 ; 56-80
2019-11-02
25 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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