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http://hdl.handle.net/10609/122046
Title: Routing drones in smart cities: a biased-randomized algorithm for solving the team orienteering problem in real time
Author: Juan Pérez, Ángel Alejandro
Freixes Puig, Alfonso
Panadero Martínez, Javier  
Serrat Piè, Carles
Estrada Moreno, Alejandro
Others: Universitat Oberta de Catalunya. Internet Interdisciplinary Institute (IN3)
Euncet Business School
Universitat Politècnica de Catalunya
Universitat Rovira i Virgili
Keywords: smart cities
unmanned aerial vehicles
team orienteering problem
Issue Date: 2020
Publisher: Transportation Research Procedia
Citation: Juan, A.A., Freixes, A., Panadero, J., Serrat, C. & Estrada-Moreno, A. (2020). Routing drones in smart cities: a biased-randomized algorithm for solving the team orienteering problem in real time. Transportation Research Procedia, 47(), 243-250. doi: 10.1016/j.trpro.2020.03.095
Published in: EURO Working Group on Transportation Meeting (EWGT), Barcelona, 8-19, setembre de 2019
Project identifier: info:eu-repo/grantAgreement/2018-1-ES01-KA103-049767
info:eu-repo/grantAgreement/2017-DI-066
Also see: https://doi.org/10.1016/j.trpro.2020.03.095
Abstract: The concepts of unmanned aerial vehicles and self-driving vehicles are gaining relevance inside the smart city environment. This type of vehicles might use ultra-reliable telecommunication systems, Internet-based technologies, and navigation satellite services to decide about the routes they must follow to efficiently accomplish their mission and reach their destinations in due time. When working in teams of vehicles, there is a need to coordinate their routing operations. When some unexpected events occur in the city (e.g., after a traffic accident, a natural disaster, or a terrorist attack), coordination among vehicles might need to be done in real-time. Using the team orienteering problem as an illustrative case scenario, this paper analyzes how the combined use of extremely fast biased-randomized heuristics and parallel computing allows for 'agile' optimization of routing plans for drones and other autonomous vehicles.
Language: English
URI: http://hdl.handle.net/10609/122046
ISSN: 2352-1465MIAR
Appears in Collections:Conference lectures

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