Real-time optimization strategy for single-track high-speed train rescheduling with disturbance uncertainties: a scenario-based chance-constrained model predictive control approach

DOI10.1016/j.cor.2020.105135OpenAlexW3098138534MaRDI QIDQ2026998

Huimin Zhang, Shukai Li, Lixing Yang, Yihui Wang, Yan-Hui Wang

Publication date: 21 May 2021

Published in: Computers \& Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cor.2020.105135

zbMATH Keywords

high-speed traindisturbance uncertaintiestrain reschedulingscenario-based chance-constrained model predictive control

Mathematics Subject Classification ID

Operations research and management science (90Bxx)

Related Items (1)

Effective train routing selection for real-time traffic management: improved model and ACO parallel computing

Cites Work

• SAPI: statistical analysis of propagation of incidents. A new approach for rescheduling trains after disruptions
• An advanced real-time train dispatching system for minimizing the propagation of delays in a dispatching area under severe disturbances
• Control of systems integrating logic, dynamics, and constraints
• A variable neighbourhood search for fast train scheduling and routing during disturbed railway traffic situations
• A model predictive control approach for discrete-time rescheduling in complex central railway station areas
• Dispatching and coordination in multi-area railway traffic management
• A decision making procedure for robust train rescheduling based on mixed integer linear programming and data envelopment analysis
• An Exact Decomposition Approach for the Real-Time Train Dispatching Problem
• Model Predictive Control for Stochastic Max-Plus Linear Systems With Chance Constraints

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