Optimizing train frequencies and train routing with simultaneous passenger assignment in high-speed railway network

Abstract In a high speed railway line plan (LP), train frequencies, train routing and passenger assignment problems are usually solved sequentially, which may lower the quality of the line plan. To bridge the gap, a bi-level multi-objective mixed integer nonlinear programming model for simultaneously obtaining the optimal plan of passenger assignment and train routing is developed in this paper. The upper level model is an integer programming (IP) model with an objective of minimizing both the total train travel time and the average capacity utilization rate, while the lower level one is a model with an objective of minimizing the total travel time of passengers and maximizing the average train attendance rate for all sections. In order to obtain the solution in relatively short time, a particle swarm approach is adopted to solve the model in a large scale railway network. As a case study, the model is applied to a real world high speed railway network in China. The results show that the total travel time of passengers and trains obtained from the simultaneous optimization model can be reduced by 0.9% in comparison with the two problems solved sequentially, which indicates that the model and the solution algorithms could be useful in practice.