Imperial College London
Alternate

Panagiotis Angeloudis

Faculty of Engineering, Department of Civil and Environmental Engineering

Reader in Transport Systems and Logistics
 
 
 
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Contact

 

+44 (0)20 7594 5986p.angeloudis Website

 
 
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Location

 

337Skempton BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Escribano:2020:10.1016/j.trc.2019.11.002,
author = {Escribano, Macias J and Angeloudis, P and Ochieng, W},
doi = {10.1016/j.trc.2019.11.002},
journal = {Transportation Research Part C: Emerging Technologies},
pages = {56--80},
title = {Optimal hub selection for rapid medical deliveries using unmanned aerial vehicles},
url = {http://dx.doi.org/10.1016/j.trc.2019.11.002},
volume = {110},
year = {2020}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - 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 24h. Additionally, the proposed methodology achieves significant reductions in mission duration and battery stock requirements with respect to conservative energy estimations and other heuristics.
AU  - Escribano,Macias J
AU  - Angeloudis,P
AU  - Ochieng,W
DO  - 10.1016/j.trc.2019.11.002
EP  - 80
PY  - 2020///
SN  - 0968-090X
SP  - 56
TI  - Optimal hub selection for rapid medical deliveries using unmanned aerial vehicles
T2  - Transportation Research Part C: Emerging Technologies
UR  - http://dx.doi.org/10.1016/j.trc.2019.11.002
UR  - https://www.sciencedirect.com/science/article/pii/S0968090X18310660?via%3Dihub
UR  - http://hdl.handle.net/10044/1/75468
VL  - 110
ER  -
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