Robust Train Timetabling and Stop Planning with Uncertain Passenger Demand

The integrated Train Timetabling and Stop Planning (TTSP) problem calls for determining the optimal timetables for a given set of trains, while choosing, for each train, the subset of stations where it will stop. Both the timetable and the stop plan are determined based on the passenger demand, i.e. on the number of passengers travelling between an origin and a destination stations. In this work, we study the Robust TTSP (RTTSP), where passenger demand is considered to be uncertain, as it is often the case in real practice. We propose an Integer Linear Programming (ILP) model for RTTSP based on Light Robustness, an effective technique introduced in [Fischetti, M., and M. Monaci, Light robustness In: Ahuja RK, Möhring RH, Zaroliagis CD (eds) Robust and online large-scale optimization. Lecture Notes in Computer Science 5868 (2009), 61–84. Springer, Berlin Heidelberg]. We test the proposed ILP model on real-world data of the Wuhan-Guangzhou high-speed railway corridor under different demand scenarios.