An Integrated Approach to Schedule Passenger Train Plans and Train Timetables Economically Under Fluctuating Passenger Demands

Chang Han, Leishan Zhou, Zixi Bai (), Wenqiang Zhao and Lu Yang
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Chang Han: School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
Leishan Zhou: School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
Zixi Bai: School of Logistics, Beijing Wuzi University, Beijing 101149, China
Wenqiang Zhao: School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
Lu Yang: Shudao Investment Group Co., Ltd., Chengdu 610000, China

Sustainability, 2025, vol. 17, issue 6, 1-30

Abstract: High-speed railways (HSRs), with their advantages of safety, energy conservation, and convenience, are increasingly becoming the preferred mode of transportation. Railway operators schedule full-schedule timetables to operate as many trains and serve as many passengers as possible. However, due to the fluctuation in passenger demands, it is not necessary to operate all trains in full-schedule timetable, which results in high operation costs and too much energy consumption. Based on this, we propose an integrated approach to schedule passenger train plans and train timetables by selecting trains to operate from the full-schedule timetable, adjusting their stopping scheme and operation sequence to reduce operation costs and energy consumption and contribute to sustainable development. In the scheduling process, both operation costs and passenger service quality are considered, and a two-objective model is established. An algorithm is designed based on Non-dominated Sorting Genetic Algorithms-II (NSGA-II) to solve the model, containing techniques for acceleration that utilize overtaking patterns, in which overtaking chromosomes are used to illustrate the train operation sequence, and parallel computing, in which the decoding process is computed in parallel. A set of Pareto fronts are obtained to offer a diverse set of results with different operation costs and passenger service quality. The model and algorithm are verified by cases based on the Beijing–Shanghai HSR line. The results indicate that compared to the full-schedule timetable, the operation costs under three sets of passenger demands decreased by 35.4%, 27.7%, and 15.7% on average. Compared to the genetic algorithm with weighting multiple objectives and NSGA-II without acceleration techniques, the algorithm proposed in this paper with the two acceleration techniques of utilizing overtaking patterns and parallel computing can significantly accelerate the solution process, with an average reduction of 42.9% and 38.3% in calculation time, indicating that the approach can handle the integrated scheduling problem economically and efficiently.

Keywords: high-speed railway; passenger train plan; train timetable; operation costs; passenger service quality; NSGA-II; acceleration techniques (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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