Prof. Lixing Yang
State Key Laboratory of Rail Traffic Control and
Safety
Beijing Jiaotong University, China
Professor
Email: [email protected]
Qualification
2005 Ph.D., Department of Mathematical Sciences,
Tsinghua University, Beijing
2002 M.Sc., College of Mathematics and Computer,
Hebei University, Baoding, Heibei
1999 B.Sc., Department of Mathematics, Hebei
University, Baoding, Heibei
Publications(Selected)
-
Chen, H., Lin, Y., & Yang, L., et al. (2026). Real-time motion planning for virtual coupling train operations: A learning-based combinatorial optimization method. Engineering Applications of Artificial Intelligence, 181, Article 115529.
-
Zhang, J., Yang, L., & Ma, W., et al. (2026). Special issue on AI-driven prediction and optimisation for smart rail transit systems. Transportmetrica A: Transport Science, 1–6.
-
Chen, Z., Yang, L., & Zhou, H., et al. (2026). Efficient optimization of train timetable and rolling stock circulation plans for urban rail transit lines under a flexible train composition mode. Computers & Operations Research, 185, Article 107587.
-
Yuan, Y., Yang, L., & D'Ariano, A., et al. (2026). Coordinating transfers between bus and metro train in real time: A logic-based branch-and-bound method. Transportation Research Part B: Methodological, 207, Article 103432.
-
Zhang, S., Zhang, J., & Deng, C., et al. (2025). Deep learning-based short-term origin-destination demand prediction in urban rail transit systems during holidays. Transportmetrica B: Transport Dynamics, 13(1), Article 2521366.
-
Chen, Z., Yang, L., & Gao, Z., et al. (2025). Hierarchical model predictive control for automatic high-speed train operation with multiple traction/braking units. Transportmetrica B: Transport Dynamics, 13(1), Article 2515487.
-
He, J., Yang, L., & Gao, Z., et al. (2025). Joint optimization of train timetable and rolling stock circulation plan with flexible composition and skip-stop strategies for co-transportation of passenger and freight. Engineering.
-
Liu, Z., Yang, L., & Zhou, H., et al. (2026). Balancing system service quality and resilience for urban rail networks: Preventive train timetabling with disruptions. Transportation Research Record, 2680(2), 920–937.
-
Wang, H., Yang, L., & Zhou, H. (2025). Enhancing efficiency and fairness: Rolling stock scheduling with virtual coupling and short-turning strategies. Transportation Science, 59(6), 1303–1328.
-
Ji, H., Yang, L., & D'Ariano, A., et al. (2025). A data-driven optimization approach for the integrated train scheduling and maintenance planning in high-speed railways. Computers & Operations Research, 175, Article 107261.
-
Yang, K., Yang, L., & Gao, Z., et al. (2025). Data-driven Wasserstein distributionally robust train formation and passenger flow control on an overcrowded metro line. Applied Mathematical Modelling, 142, Article 116330.
-
Zhang, C., Yang, L., & Gao, Z., et al. (2025). Integrated optimisation of train stop planning and timetabling in a railway network: A stochastic optimisation approach. Transportmetrica A: Transport Science, 21(1), 1–43.
-
Lian, D., Yang, L., & Gao, Z., et al. (2025). Energy-efficient multi-curve optimization in urban rail transit: Stability enhancement under operational uncertainties and curve adjustments. Transportation Research Part C: Emerging Technologies, 176, Article 105148.
-
Yuan, Y., Yang, L., & D'Ariano, A., et al. (2025). Nonlinear model predictive control for electric bus operations based on generalized disjunctive programming method. IEEE Transactions on Control Systems Technology, 33(5), 1820–1834.
-
Yin, J., D'Ariano, A., & Yang, L., et al. (2026). Real-time rolling stock and timetable rescheduling in urban rail transit systems. INFORMS Journal on Computing, 38(2), 507–530.
-
Mo, Y., Zhang, J., & Wang, C., et al. (2025). A semi-conv-transformer model for inflow prediction of newly expanding subway lines. IEEE Transactions on Intelligent Transportation Systems, 26(6), 8497–8512.
-
Tian, X., & Yang, L. (2025). How to improve transportation capacity of oversaturated metro lines? A flexible operation approach with extra-long train compositions. Transportation Research Part B: Methodological, 195, Article 103188.
-
Yuan, Y., Yang, L., & D'Ariano, A., et al. (2025). Dynamic bus bridging strategy in response to metro disruptions integrated with routing, timetabling and vehicle dispatching. Omega, 134, Article 103287.
-
Qi, J., Yang, L., & Gao, Z., et al. (2025). Joint optimization of train stop planning and timetabling with time-dependent passenger and freight demands in high-speed railway. Transportation Research Part C: Emerging Technologies, 172, Article 105025.
-
Zhang, Y., Yang, L., & Gao, Z., et al. (2025). Multi-step look ahead deep reinforcement learning approach for automatic train regulation of urban rail transit lines with energy-saving. Engineering Applications of Artificial Intelligence, 145, Article 110181.
Profile Details
http://faculty.bjtu.edu.cn/7856/
https://www.researchgate.net/profile/Lixing-Yang
https://scispace.com/authors/lixing-yang-1ms7xs7etc
WOS ResearcherID: JPK-4476-2023