Macroscopic Real-Time Timetable Rescheduling Approach for High-Speed Railway under Complete Blockages Using a Three-Stage Algorithm. Issue 3 (March 2022)

• Record Type: Journal Article
• Authors: Gao, Bowen; Dong, Decun; Wu, Yusen; Ou, Dongxiu
• Is Part Of: Transportation research record. Volume 2676:Issue 3(2022)
• Page Start: 535
• Page End: 550
• Publication Date: 2022-03
• Subjects: high-speed railway -- disruption management -- timetable rescheduling -- linear programming; Transportation -- Periodicals; Roads; Transport -- Périodiques; Routes -- Périodiques; Routes -- Conception et construction -- Périodiques; Roads; Transportation; 388.05
• DOI: 10.1177/03611981211052960
• Languages: English
• ISSNs: 0361-1981

Abstract

The rescheduling of train timetables under a complete blockage is a challenging process, which is more difficult when timetables contain lots of trains. In this paper, a mixed integer linear programming (MILP) model is formulated to solve the problem, following the rescheduling strategy that blocked trains wait inside the stations during the disruption. When the exact end time of the disruption is known, trains at stations downstream of the blocked station can depart early. The model aims at minimizing the total delay time and the total number of delayed trains under the constraints of station capacities, activity time, overtaking rules, and rescheduling strategies. Because there are too many variables and constraints of the MILP model to be solved, a three-stage algorithm is designed to speed up the solution. Experiments are carried out on the Beijing–Guangzhou high-speed railway line from Chibibei to Guangzhounan. The original timetable contains 162 trains, including 29 cross-line trains and 133 local trains. The simulation results show that our model can handle the optimization task of the timetable rescheduling problem very well. Compared with the one-stage algorithm, the three-stage algorithm is proved to greatly improve the solving speed of the model. All instances can get a better optimized disposition timetable within 450 to 600 s, which is acceptable for practical use.