Air and high-speed rail (AH) integration services are gaining ground with the development of the high-speed railway and airline industries. A well-designed feeder train timetable with good synchronization is of great significance in an AH integration service, because it can improve the connectivity at transfer nodes and offer more opportunities for intermodal passengers to travel. In this study, we propose a multi-objective model of a feeder railway timetable problem in an AH integration service to improve synchronization. The aims of the optimization model are to maximize the number of synchronizations and the coverage of synchronized flights, as well as to minimize the transfer penalties of passengers. We focus on a scenario of a partial subnetwork in which one direction of a two-direction railroad line with one transfer station is considered. The model is applied to Shijiazhuang Zhengding International Airport, China. The results illustrate the effectiveness of the approach developed in the paper.

China Railway Corporation (CRC) has been paid more attention to passenger transportation revenue, with its increase proportion in transportation revenue. Due to the price regulation, the only way CRC can improve ticket sale profit is to find a best seat allocation scheme. This study focuses on the optimization of railway revenue management problem in China with consideration of i) customer behaviors including their arrival and purchase preferences, ii) a specific ticket booking mechanism called “seat-based control”. To evaluate the performance of seat-based control, we build a Discrete-Time Markov Chain model to describe the ticket reservation process and then design a genetic algorithm to find approximate solutions. The performance of proposed method is tested in two experiments with two other benchmarks. Finally, we apply it to practical data of the Nanning-Guangzhou high-speed railway line.

Railways around the world are experiencing growth in traffic flow, but the problem concerning how to optimize the utilization of capacity is still demands significant research. To accommodate the increasing traffic demand, the high-speed railway operator in China is interested in understanding the potential benefit of adopting reasonable headway to balance the safety and efficiency of train operations. In this study, a compress timetable scheduling model based on the UIC Code 406 method is presented to evaluate the line capacity. In this model, train headway is not pre-fixed as in the existing research, but considers the actual operating conditions and is calculated using actual running data. The results of the case study show that refined headway calculations generally have positive capacity effects.

Railway seat inventory control aims to maximize ticket sale profits by determining a selling policy on the reservation horizon. This paper introduces a dynamic bid price approach in railway seat inventory control problem. Multi-dimensional demand is taken into consideration in modeling the problem, in which passenger transfer is our main focus. A new approximate approach is designed to this problem. Numerical examples are presented to evaluate the efficiency of this approach. Simulation experiments are conducted to verify the impact of transfer under different scenarios.

In China, cross-track high-speed trains (CTHSTs) play an important role in railway passenger transportation, with an increasing number of cross-track passengers sourced from the expansion of high-speed railway (HSR) network. The CTHST generally has long travel times, so running CTHSTs is not beneficial for train rescheduling work and plan’s periodicity in the periodic operation context. Thus, the main challenge in cross-track line planning is looking for a symmetry point between passenger transportation and disadvantages of running CTHSTs, which are two conflicting aspects. In this study, we developed a multiobjective integer programming model to produce a balanced cross-track line plan by combining individual-track high-speed trains (ITHSTs) into CTHSTs, which is a discrete optimization problem. This strikes a balance among four goals: the periodicity of the line plan, CTHST quantity, CTHST mileage, and CTHST stops in the context of periodic operation, while satisfying the constraints of passenger demand and the number of available ITHSTs. Numerical experiments are conducted based on a real-world network and optimal solutions were quickly obtained. We analyzed impacts of each goal and parameter on the result and influencing factors of computation. Comparisons with existing methods and real-life plans were also presented to show improvements made by proposed model.