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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, Angel A. 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 (UPC) Universitat Rovira i Virgili (URV) |
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 |
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. |
Keywords: | smart cities unmanned aerial vehicles team orienteering problem |
DOI: | 10.1016/j.trpro.2020.03.095 |
Document type: | info:eu-repo/semantics/conferenceObject |
Issue Date: | 2020 |
Publication license: | http://creativecommons.org/licenses/by-nc-nd/4.0/es/ |
Appears in Collections: | Conferències |
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Juan_TRP_Routing_Drones.pdf | 506,07 kB | Adobe PDF | View/Open |
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