Train rescheduling in a major disruption on a high-speed railway network with seat reservation - Zhan, Shuguang; Wong, S. C.; Shang, Pan; Lo, S. M. (Transportmetrica (Abingdon, Oxfordshire, UK), 2022)
In this paper, we develop a method of real-time train rescheduling on double-track high-speed railway lines undergoing major disruption. As a result, trains approaching the disrupted area cannot use the blocked tracks and must be efficiently rescheduled. As most tracks in a high-speed railway station can be shared by trains arriving from both directions, we reschedule both inbound and outbound trains simultaneously by allowing them to share sidings. Based on a space-time network, an integer linear programming (ILP) model is formulated to minimize the train-deviation cost. As the ILP model is difficult to solve for real-world problems, we decompose it into many easy-to-solve subproblems by the alternating direction method of multipliers (ADMM) algorithm. Our model is tested on an abstract representation of the Chinese high-speed railway system to illustrate both the benefit of rescheduling trains in both directions simultaneously and the efficiency of the ADMM algorithm in train rescheduling.