Routing Drones in Smart Cities: a Biased-Randomized Algorithm for Solving the Team Orienteering Problem in Real Time

• DOI: 10.1016/j.trpro.2020.03.095
• Publication Date: 2020-04-25T15:06:48Z
• Authors: A.A. Juan; A. Freixes; J. Panadero; C. Serrat; A. Estrada-Moreno
• Keywords: Orienteering; Drone; Heuristics; Payload (computing); Relevance; Vehicle Routing Problem

The concepts of unmanned aerial vehicles and self-driving are gaining relevance inside the smart city environment. This type might use ultra-reliable telecommunication systems, Internet-based technologies, navigation satellite services to decide about routes they must follow efficiently accomplish their mission reach destinations in due time. When working teams vehicles, there is a need coordinate routing operations. some unexpected events occur (e.g., after traffic accident, natural disaster, or terrorist attack), coordination among be done real-time. Using team orienteering problem as an illustrative case scenario, this paper analyzes how combined extremely fast biased-randomized heuristics parallel computing allows for 'agile' optimization plans drones other autonomous vehicles.