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Title	Routing Drones In Smart Cities: A Biased-Randomized Algorithm For Solving The Team Orienteering Problem In Real Time
ID_Doc	47093
Authors	Juan A.A.; Freixes A.; Panadero J.; Serrat C.; Estrada-Moreno A.
Year	2020
Published	Transportation Research Procedia, 47
DOI	http://dx.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. © 2020 The Authors. Published by Elsevier B.V.
Author Keywords	smart cities; team orienteering problem; unmanned aerial vehicles

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