Train schedule optimization based on schedule-based stochastic passenger assignment

• Published in: Transportation research. Part E, Logistics and transportation review Vol. 136; p. 101882
• Main Authors: Xie, J., Wong, S.C., Zhan, S., Lo, S.M., Chen, Anthony
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.04.2020
• Subjects: Mixed itinerary-size weibit model; Schedule-based; Train scheduling; Schedule-based; Train scheduling; Mixed itinerary-size weibit model
• ISSN: 1366-5545; 1878-5794
• DOI: 10.1016/j.tre.2020.101882

•A model is developed for both stochastic passenger assignment and train scheduling.•The mixed itinerary-size weibit model is applied to the passenger assignment module.•An iterative method is introduced to efficiently solve the resultant model.•The model is tested on a real-world high-speed railway network in Southern China. In this study, we propose a new schedule-based itinerary-choice model, the mixed itinerary-size weibit model, to address the independently and identically distributed assumptions that are typically used in random utility models and heterogeneity of passengers’ perceptions. Specifically, the Weibull distributed random error term resolves the perception variance with respect to various itinerary lengths, an itinerary-size factor term is suggested to solve the itinerary overlapping problem, and random coefficients are used to model heterogeneity of passengers. We also apply the mixed itinerary-size weibit model to a train-scheduling model to generate a passenger-oriented schedule plan. We test the efficiency and applicability of the train-scheduling model in the south China high-speed railway network, and we find that it works well and can be applied to large real-world problems.