研究论文
Approximate dynamic programming approach to efficient metro train timetabling and passenger flow control strategy with stop-skipping
Yunfeng Zhang, Shukai Li, Yin Yuan, Jinlei Zhang, Lixing Yang
Beijing Jiaotong University
来源Engineering Applications of Artificial Intelligence
年份2023
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学术脉络
学科主题
工程Railway Systems and Energy Efficiency
Transportation Planning and Optimization · Elevator Systems and Control
参考文献 52
Energy-Efficient Driving Strategy for Freight Trains Based on Power Consumption Analysis
被引 37Yun Bai, Baohua Mao, Fangming Zhou · Journal of Transportation Systems Engineering and Information Technology · 2009
Multi objective particle swarm optimization algorithm for the design of efficient ATO speed profiles in metro lines
被引 131M. Domínguez, Antonio Fernández-Cardador, Asunción P. Cucala · Engineering Applications of Artificial Intelligence · 2014
Exact formulations and algorithm for the train timetabling problem with dynamic demand
被引 236Eva Barrena, David Canca, Leandro C. Coelho · Computers & Operations Research · 2013
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引用本文 21
Adaptive rescheduling of rail transit services with short-turnings under disruptions via a multi-agent deep reinforcement learning approach
被引 23Cheng-shuo Ying, Andy H.F. Chow, Yimo Yan · Transportation Research Part B Methodological · 2024
Collaborative optimization of passenger flow control and bus-bridging services in commuting metro lines
被引 14Xiangjiang Li, Yahan Lu, Lixing Yang · Applied Mathematical Modelling · 2024
Multi-step look ahead deep reinforcement learning approach for automatic train regulation of urban rail transit lines with energy-saving
被引 9Yunfeng Zhang, Shukai Li, Yin Yuan · Engineering Applications of Artificial Intelligence · 2025
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