Deep dispatching: A deep reinforcement learning approach for vehicle dispatching on online ride-hailing platform
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DOI: 10.1016/j.tre.2022.102694
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- Wang, Jiawei & Guo, Qinglai & Sun, Hongbin, 2024. "Planning approach for integrating charging stations and renewable energy sources in low-carbon logistics delivery," Applied Energy, Elsevier, vol. 372(C).
- Wang, Tao & Guo, Jia & Zhang, Wei & Wang, Kai & Qu, Xiaobo, 2024. "On the planning of zone-based electric on-demand minibus," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 186(C).
- Xiangyu Huang & Yan Cheng & Jing Jin & Aiqing Kou, 2024. "Research on Dynamic Subsidy Based on Deep Reinforcement Learning for Non-Stationary Stochastic Demand in Ride-Hailing," Sustainability, MDPI, vol. 16(15), pages 1-25, July.
- Wu, Weitiao & Zhu, Yanchen & Liu, Ronghui, 2024. "Dynamic scheduling of flexible bus services with hybrid requests and fairness: Heuristics-guided multi-agent reinforcement learning with imitation learning," Transportation Research Part B: Methodological, Elsevier, vol. 190(C).
- Si, Jinhua & He, Fang & Lin, Xi & Tang, Xindi, 2024. "Vehicle dispatching and routing of on-demand intercity ride-pooling services: A multi-agent hierarchical reinforcement learning approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 186(C).
- Omar Al-Ani & Sanjoy Das, 2022. "Reinforcement Learning: Theory and Applications in HEMS," Energies, MDPI, vol. 15(17), pages 1-37, September.
- Nie, Fapeng & Li, Xiang & Zhou, Chang, 2024. "Impact of privacy regulation involving information collection on the ride-hailing market," Omega, Elsevier, vol. 126(C).
- Gao, Chang & Lin, Xi & He, Fang & Tang, Xindi, 2024. "Online relocating and matching of ride-hailing services: A model-based modular approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 188(C).
- Ao, Di & Lai, Zhijie & Li, Sen, 2024. "Control of dynamic ride-hailing networks with a mixed fleet of autonomous vehicles and for-hire human drivers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 189(C).
- Liu, Chengqi & Wang, Zelin & Liu, Zhiyuan & Huang, Kai, 2025. "Multi-Agent reinforcement learning framework for addressing Demand-Supply imbalance of Shared Autonomous Electric Vehicle," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 197(C).
- Lu Yang & Leishan Zhou & Hanxiao Zhou & Chang Han & Wenqiang Zhao, 2023. "A Lagrangian Method for Calculation of Passing Capacity on a Railway Hub Station," Mathematics, MDPI, vol. 11(6), pages 1-20, March.
- Tao Wang & Dayi Qu & Hui Song & Shouchen Dai, 2023. "A Hierarchical Framework of Decision Making and Trajectory Tracking Control for Autonomous Vehicles," Sustainability, MDPI, vol. 15(8), pages 1-28, April.
- Zhao, Zhonghao & Lee, Carman K.M. & Yan, Xiaoyuan & Wang, Haonan, 2024. "Reinforcement learning for electric vehicle charging scheduling: A systematic review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 190(C).
- Huang, Yunping & Zhu, Pengbo & Zhong, Renxin & Geroliminis, Nikolas, 2024. "A bi-level approach for optimal vehicle relocating in Mobility-On-Demand systems with approximate dynamic programming and coverage control," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 192(C).
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Keywords
Vehicle dispatching; Deep reinforcement learning; Load balancing;All these keywords.
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