![]()
-
Robust train timetabling based on realized operations: a data-driven prediction-optimization framework. Huang Ping, D’ariano Andrea, Yang Yuxiang, Lu Gongyuan, Li Zhongcan, Corman Francesco..Transportation Research Part E: Logistics and Transportation Review, 2026, 213: 104923.,2026
-
Train timetable rescheduling considering potential train operation conflicts: an enhanced deep reinforcement learning approach. Luo Jie, Huang Ping**, Li Zhongcan, Pang Zishuai, D’ariano Andrea..International Journal of Rail Transportation, 2026: 1-32.,2026
-
Integrating graph and neural relational inference for network-wide train delay prediction: An equilibrium between accuracy and interpretability. Li Zhongcan, Dong Wei, Ji Yindong, Luo Jie, Huang Ping**..Transportation Research Part C: Emerging Technologies, 2026, 182: 105418.,2026
-
Solving the railway timetable rescheduling problem with graph neural networks. Huang Ping, Peng Zihuan, Li Zhongcan, Peng Qiyuan..Railway Engineering Science, 2025: 1-22.,2025
-
Probabilistic Modeling of Train Operations for Uncertainty Quantification: A Context-Aware Bayesian Network Approach,Ping Huang,Francesco Corman.IEEE Transactions on Intelligent Transportation Systems,2024
