Approximate dynamic programming for planning a ride-hailing system using autonomous fleets of electric vehicles
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DOI: 10.1016/j.ejor.2020.01.033
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- Cervellera, Cristiano, 2023. "Optimized ensemble value function approximation for dynamic programming," European Journal of Operational Research, Elsevier, vol. 309(2), pages 719-730.
- Yu, Guodong & Liu, Aijun & Zhang, Jianghua & Sun, Huiping, 2021. "Optimal operations planning of electric autonomous vehicles via asynchronous learning in ride-hailing systems," Omega, Elsevier, vol. 103(C).
- Chen, Yao & Liu, Yang & Bai, Yun & Mao, Baohua, 2024. "Real-time dispatch management of shared autonomous vehicles with on-demand and pre-booked requests," Transportation Research Part A: Policy and Practice, Elsevier, vol. 181(C).
- Zhou, Yaqian & Yang, Hai & Ke, Jintao & Wang, Hai & Li, Xinwei, 2022. "Competition and third-party platform-integration in ride-sourcing markets," Transportation Research Part B: Methodological, Elsevier, vol. 159(C), pages 76-103.
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- Fleckenstein, David & Klein, Robert & Steinhardt, Claudius, 2023. "Recent advances in integrating demand management and vehicle routing: A methodological review," European Journal of Operational Research, Elsevier, vol. 306(2), pages 499-518.
- Tang, Xindi & Yang, Jie & Lin, Xi & He, Fang & Si, Jinhua, 2023. "Dynamic operations of an integrated mobility service system of fixed-route transits and flexible electric buses," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 173(C).
- Guo, Xiaotong & Caros, Nicholas S. & Zhao, Jinhua, 2021. "Robust matching-integrated vehicle rebalancing in ride-hailing system with uncertain demand," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 161-189.
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Keywords
Approximate dynamic programming; Ride-Hailing; Autonomous vehicles; Surge pricing; Adaptive learning;All these keywords.
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