Optimal hub selection for rapid medical deliveries using unmanned aerial vehicles
File(s)R16 - Manuscript.pdf (2.52 MB)
Accepted version
Author(s)
Escribano Macias, Jose
Angeloudis, Panagiotis
Ochieng, Washington
Type
Journal Article
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.
Date Issued
2020-01-01
Date Acceptance
2019-11-02
Citation
Transportation Research Part C: Emerging Technologies, 2020, 110, pp.56-80
ISSN
0968-090X
Publisher
Elsevier BV
Start Page
56
End Page
80
Journal / Book Title
Transportation Research Part C: Emerging Technologies
Volume
110
Copyright Statement
© 2019 Elsevier Ltd. All rights reserved. This manuscript is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence http://creativecommons.org/licenses/by-nc-nd/4.0/
Sponsor
Engineering and Physical Sciences Research Council
Identifier
https://www.sciencedirect.com/science/article/pii/S0968090X18310660?via%3Dihub
Subjects
09 Engineering
08 Information and Computing Sciences
15 Commerce, Management, Tourism and Services
Logistics & Transportation
Publication Status
Published
Date Publish Online
2019-11-26