Resumen
This paper considers the problem of supporting immediate response operations after a disaster with information about the available road network to reach certain locations. We propose an online algorithm that aims to minimize the route length required by an unmanned aerial vehicle (UAV) to explore the road accessibility of potential victim locations. It is assumed that no information about disrupt ...
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This paper considers the problem of supporting immediate response operations after a disaster with information about the available road network to reach certain locations. We propose an online algorithm that aims to minimize the route length required by an unmanned aerial vehicle (UAV) to explore the road accessibility of potential victim locations. It is assumed that no information about disruptions in the road network is available at the start of the exploration. The online algorithm applies two movement and three orientation strategies. Additionally, a cutting strategy is used to restrict the search space after new information about the state of single roads is obtained. We consider a road and an aerial network for the movements of the UAV, since it is not necessary to follow the route of a road any longer, if it can be marked as disrupted. In extensive numerical studies with artificial and real-world test instances, it is evaluated for different disruption levels, which combinations of movement and orientation strategies perform best. Additionally, we propose different refuelling strategies for the UAV and present how they differ in the number of refuelling operations and the required additional route length. The results show that an efficient online algorithm can save valuable exploration time. [--]
Materias
Aerial vehicles for humanitarian operations,
Disaster management,
Disrupted road network,
Immediate response operations,
Online algorithm,
Online exploration strategies
Publicado en
OR Spectrum (2021) 43:289–326
Departamento
Universidad Pública de Navarra/Nafarroako Unibertsitate Publikoa. Institute of Smart Cities - ISC
Entidades Financiadoras
This work has been partially supported by the Österreichische Nationalbank (OeNB) (17703) and the Erasmus+ Program (2018-1-ES01-KA103-049767). We also acknowledge the support of the UPNA doctoral program and the PID2019-111100RB-C22/AEI/10.13039/501100011033 project.