Using Transformers and Reinforcement Learning for the Team Orienteering Problem Under Dynamic Conditions

Using Transformers and Reinforcement Learning for the Team Orienteering Problem Under Dynamic Conditions

This paper presents a reinforcement learning (RL) approach for solving the team orienteering problem under both deterministic and dynamic travel time conditions. The proposed method builds on the transformer architecture and is trained to construct routes that adapt to real-time variations, such as...

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Bibliographic Details
Main Authors: Antoni Guerrero, Marc Escoto, Majsa Ammouriova, Yangchongyi Men, Angel A. Juan
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Mathematics
Subjects:
team orienteering problem
reinforcement learning
dynamic conditions
model generalization
Online Access:https://www.mdpi.com/2227-7390/13/14/2313
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