Solving the probabilistic drone routing problem : searching for victims in the aftermath of disasters.
Several major industrial disasters happen each year around the world. They usu- ally involve limited accessibility, poor ground conditions, and toxic wastes. As a consequence, this reduces the efficiency of humanitarian operations. In such a con- text, flying drones may be a viable alternative: fast...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2024 |
| País: | Brasil |
| Institución: | Universidade Federal de Ouro Preto (UFOP) |
| Repositorio: | Repositório Institucional da UFOP |
| Idioma: | inglés |
| OAI Identifier: | oai:repositorio.ufop.br:123456789/19195 |
| Acceso en línea: | https://www.repositorio.ufop.br/handle/123456789/19195 https://doi.org/10.1002/net.22214 |
| Access Level: | acceso abierto |
| Palabra clave: | Disaster logistics Drone routing problem Heuristics Search planning |
| Sumario: | Several major industrial disasters happen each year around the world. They usu- ally involve limited accessibility, poor ground conditions, and toxic wastes. As a consequence, this reduces the efficiency of humanitarian operations. In such a con- text, flying drones may be a viable alternative: faster, no dependency on ground conditions, and larger areas scanned. They are also better suited for following the population and the crisis dynamic. For such a purpose, various issues have to be addressed such as defining and optimizing the drone’s routes, their energy consump- tion, choosing the relay points for recharging equipment, among others. In this study, several additional features from existing works are considered: first, a probability of identifying individuals is defined. Thus, each node can be scanned several times in order to improve the observation. In addition, the nodes are prioritized accord- ing to a given heatmap. The probabilistic drone routing problem (PDRP) consists of finding a route, that is, a sequence of trips, for each drone such that the sum of the expected number of identified individuals on all routes is maximized. Constraints on energy consumption, collision avoidance and drone-base assignment are considered. We propose a heuristic and metaheuristics based on the adaptive large neighborhood search for the PDRP. The methods are tested on theoretical instances, as well as on a case study of the Beirut Port explosion on August 4, 2020, in order to analyze the performance of the proposed methods. |
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