Chinese high-speed railways faced a fast development in recent years. Their performances are still confronted with disruptions unavoidably, which impact on the reliability of the traffic and passenger satisfaction. This paper presents a rescheduling model which is able to solve the critical problem of effective disruption management (namely, fast and dynamic train speed adaptation, supervision of braking and changing train sequence due to incidents, warnings or alarms), and consider in detail the signalling and safety systems based on a quasi-moving block system with variable headways. We integrate the modelling of efficient traffic management measures and the supervision of speed, braking and headway in one general job-shop model. We use a commercial solver with a custom-designed two-step method to speed up the procedure in order to solve instances from real-world high-speed networks in China quickly. Overall, the approach guarantees the resolution of the traffic control and speed management within few minutes of computation time. The output demonstrates that the proposed approach can achieve a reduction of train delays by 70% compared to the solution determined by keeping the order of the original timetable, and get the optimality for more than 90% of instances with a realistic case.

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Research focused on the real-time rescheduling of high-speed railway traffic with a quasi-moving blocking system and transition process affected by the entrance delays and disruptions determining speed limitation. A mixed-integer linear program model related to a job shop model of operations is formulated to reduce the final delay (tardiness) of trains, where three objective functions combine different manners related to traffic control and speed management. The dynamic interaction between train speed and distance headway is considered in the model. Through experiments on a real-world high-speed line in China, the solution quality of the model is assessed by the delay distribution of trains or the smooth degree of train speed profile. The model manages to optimize traffic in the transition from a disordered condition (when disruptions appear) to a normal condition (after disruptions) for real-time operations. In conclusion, there are two and three transition phases for the cases without and with entrance delays, respectively, seen by analyzing the deviation between the rescheduled and planned timetables.@en

Chinese high-speed railways faced large development in the recent years. Their performance is still confronted with disruptions, which impact the traffic and the passengers. With the aim to better understand the influences of the sources of disruptions, we study the statistical characteristics of the causes of disruptions and delayed traffic. We use maximum likelihood estimation to determine the probability density distribution of the different disruption source. A zero-truncated negative binomial distribution model is then developed to link the sources of disruptions and the amount of delayed traffic. This is important to determine the probability and the impact of disruptions sources. We can then suggest which disruption sources should be tackled in order to reduce impact and probability of disruptions.

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