Combining Parallel Computing and Biased Randomization for Solving the Team Orienteering Problem in Real-Time

نویسندگان

چکیده

In smart cities, unmanned aerial vehicles and self-driving are gaining increased concern. These might utilize ultra-reliable telecommunication systems, Internet-based technologies, navigation satellite services to locate their customers other team plan routes. Furthermore, the of should serve by specified due date efficiently. Coordination between be needed accomplished in real-time exceptional cases, such as after a traffic accident or extreme weather conditions. This paper presents planning vehicle routes orienteering problem. addition, an ‘agile’ optimization algorithm is presented these for drones autonomous vehicles. combines extremely fast biased-randomized heuristic parallel computing approach.

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One of the problems tourism faces is how to make itineraries more effective and efficient. This research has solved the routing problem with the objective of maximizing the score and minimizing the time needed for the tourist’s itinerary. Maximizing the score means collecting a maximum of various kinds of score from each destination that is visited. The profits differ according to whether those...

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The Team Orienteering Problem (TOP) is defined as to find a set of vehicle walks such that the total collected reward received from visiting a subset of customers is maximized and the length of each vehicle walk is restricted by a pre-specified limit. The team orienteering problem with capacity constraint and time window(TOPCT) is an extension of the TOP where each customer has a demand and a t...

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ژورنال

عنوان ژورنال: Applied sciences

سال: 2021

ISSN: ['2076-3417']

DOI: https://doi.org/10.3390/app112412092