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This problem involves determining the most effective and efficient routes using limited vehicles and resources to offer responsive door-to-door transportation services for users with specific needs. Logistics service providers require systems that can deliver optimal solutions to these combinatorial problems within a reasonable time. Recently, there has been a significant increase in the use of artificial intelligence optimization algorithms such as meta-heuristics or learning-based approaches to solve such problems. Among the learning-based approaches, reinforcement learning  has gained prominence for routing and scheduling tasks, owing to its ability to adaptively learn from complex state spaces and dynamically changing environments. In this study, a novel transformer-based deep reinforcement learning method is proposed to solve the Dial and Ride problem for a single service vehicle. In the proposed model, we adopt a modified transformer architecture instead of employing traditional linear layers, we integrate convolutional layers. To validate our approach, we conduct comprehensive experiments comparing our method against four well-known metaheuristic algorithms and a Deep Q-Network algorithm. The results indicate that proposed approach outperforms these techniques in terms of shorter total travel distances. Additionally, the proposed method is tested on a real-world scenario generated in the Buyukdere neighborhood of Eskisehir. The results demonstrate that the proposed method makes it possible to solve the problem within a reasonable time. This study confirms that the proposed deep reinforcement learning method can effectively address the Dial-a-Ride Problems.<\/jats:p>","DOI":"10.1007\/s10115-025-02493-4","type":"journal-article","created":{"date-parts":[[2025,6,13]],"date-time":"2025-06-13T05:44:40Z","timestamp":1749793480000},"page":"9085-9109","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A transformer-based deep reinforcement learning for the Dial-a-Ride problem"],"prefix":"10.1007","volume":"67","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7688-9326","authenticated-orcid":false,"given":"\u00d6zge","family":"Aslan Y\u0131ld\u0131z","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3528-7342","authenticated-orcid":false,"given":"\u0130nci","family":"Sar\u0131\u00e7i\u00e7ek","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5589-2032","authenticated-orcid":false,"given":"Ahmet","family":"Yaz\u0131c\u0131","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,6,13]]},"reference":[{"issue":"1","key":"2493_CR1","doi-asserted-by":"publisher","first-page":"80","DOI":"10.1287\/mnsc.6.1.80","volume":"6","author":"GB Dantzig","year":"1959","unstructured":"Dantzig GB, Ramser JH (1959) The truck dispatching problem. 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