Download PDFOpen PDF in browserRobust Optimization of Train Timetable with Short-Turning Strategy Considering Uncertain Passenger Demand and Vehicle SelectionEasyChair Preprint 987423 pages•Date: March 17, 2023AbstractConsidering the uncertainty of passenger demand and vehicle selection, this paper investigates a robust optimization approach for the train timetabling problem with short-turning strategy in urban rail transit system. With the scenario-based representation of passenger distribution, a mixed-integer linear programming (MILP) model is formulated that simultaneously integrates train timetabling, short-turning strategy and rolling stock circulation. The proportion of passengers who take the short-turning train services to the last station of the short-turning region and transfer to the full-length train services to their destination stations, is introduced to describe the passenger vehicle selection behavior under short-turning strategy. Finally, three experiments are designed for Xi’an Metro Line 3 to verify the solution quality and effectiveness of the proposed methods. The results indicate that the robust train timetable can more effectively satisfy multi-scenario passenger demand than the satisfactory train timetable generated by independent optimization of each demand scenario. Keyphrases: robust optimization, short-turning strategy, train timetable, uncertain passenger demand, vehicle selection
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