In this section
Below is a list of all relevant publications authored by Robotics Forum members.
@article{Escribano:2020:10.1007/s00291-020-00602-z,
author = {Escribano, Macias J and Goldbeck, N and Hsu, P-Y and Angeloudis, P and Ochieng, W},
doi = {10.1007/s00291-020-00602-z},
journal = {OR SPECTRUM},
pages = {1089--1125},
title = {Endogenous stochastic optimisation for relief distribution assisted with unmanned aerial vehicles},
url = {http://dx.doi.org/10.1007/s00291-020-00602-z},
volume = {42},
year = {2020}
}
TY - JOUR
AB - Unmanned aerial vehicles (UAVs) have been increasingly viewed as useful tools to assist humanitarian response in recent years. While organisations already employ UAVs for damage assessment during relief delivery, there is a lack of research into formalising a problem that considers both aspects simultaneously. This paper presents a novel endogenous stochastic vehicle routing problem that coordinates UAV and relief vehicle deployments to minimise overall mission cost. The algorithm considers stochastic damage levels in a transport network, with UAVs surveying the network to determine the actual network damages. Ground vehicles are simultaneously routed based on the information gathered by the UAVs. A case study based on the Haiti road network is solved using a greedy solution approach and an adapted genetic algorithm. Both methods provide a significant improvement in vehicle travel time compared to a deterministic approach and a non-assisted relief delivery operation, demonstrating the benefits of UAV-assisted response.
AU - Escribano,Macias J
AU - Goldbeck,N
AU - Hsu,P-Y
AU - Angeloudis,P
AU - Ochieng,W
DO - 10.1007/s00291-020-00602-z
EP - 1125
PY - 2020///
SN - 0171-6468
SP - 1089
TI - Endogenous stochastic optimisation for relief distribution assisted with unmanned aerial vehicles
T2 - OR SPECTRUM
UR - http://dx.doi.org/10.1007/s00291-020-00602-z
UR - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000560617500001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR - https://link.springer.com/article/10.1007%2Fs00291-020-00602-z
UR - http://hdl.handle.net/10044/1/91258
VL - 42
ER -
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