Routing with Pickup and Delivery via Deep Reinforcement Learning; [Derin Pekiştirmeli Öğrenme ile Al-Bırak Rotalama]

Intelligent transportation systems are an important issue within the scope of smart cities. Vehicle routing problems, which are a combinatorial problem, need to be solved in the design of the relevant systems. In this regard, the use of artificial intelligence optimization algorithms such as meta-heuristics has increased significantly in recent years. To the best of our knowledge, there are no papers that address the Dial and Ride problem by using reinforcement learning, one of the learning-based models. In this study, the Dial and Ride problem is solved for a single service vehicle using the transformer-based deep reinforcement learning method. The proposed method is tested on a problem generated in an environment in Eskişehir Büyükdere Neighborhood. As a result of the test problem, it is shown that the proposed method produced a solution to the problem in a reasonable time. The study showed that the Dial and Ride Problems can be solved with reinforcement learning. © 2024 IEEE.