Optimizing Train Timetable Based on Departure Time Preference of Passengers for High-Speed Rails

Abstract

Passengers would like to choose the most suitable train based on their travel preferences, expenses, and train timetable in the high-speed railway corridor. Meanwhile, the railway department will constantly adjust the train timetable according to the distribution of passenger flows during a day to achieve the optimal operation cost and energy consumption saving plan. The question is how to meet the differential travel needs of passengers and achieve sustainable goals of service providers. Therefore, it is necessary to design a demand-oriented and environment-friendly high-speed railway timetable. This paper formulates the optimization of train timetable for a given high-speed railway corridor, which is based on the interests of both passengers and transportation department. In particular, a traveling time-space network with virtual departure arc is constructed to analyze generalized travel costs of passengers of each origin-destination (OD), and bilevel programming model is used to optimize the problem. The upper integer programming model regards the minimization of the operating cost, which is simplified to the minimum traveling time of total trains, as the goal. The lower level is a user equilibrium model which arranges each OD passenger flow to different trains. A general advanced metaheuristic algorithm embedded with the Frank–Wolfe method is designed to implement the bilevel programming model. Finally, a real-world numerical experiment is conducted to verify the effectiveness of both the model and the algorithm.

Commuting to work in cities: Bus, car, or train?

“…(2020) and Huang et al (2021) have pointed out that the on-train travel time can be regarded as being fixed. In addition, this fixity assumption concerning on-train travel times has also been made by Holden (1989).…”

“…Moreover, our assumption that the on-train travel time is fixed has precedents in the literature. For instance, in their analyses of alternative aspects of train travel, both Zhu et al (2020) and Huang et al (2021) pointed out that the on-train travel time can be regarded as fixed. In addition, Holden (1989) made this fixity assumption concerning on-train travel times.…”

Skip-Stop Strategy Patterns optimization to enhance mass transit operation under physical distancing policy due to COVID-19 pandemic outbreak

“…Consequently, the train schedule must be organized in such a way with reduced passenger travel times to minimize the possibility of contagion risks. As the travel time and passenger demand have been the primary concerns in establishing potential train schedules in many studies ( Rajabighamchi et al, 2019 ; Boroun et al, 2020 ; Huang et al, 2021 ; Khwanpruk et al, 2021 ; Wang et al, 2021 ; Zhang et al, 2021 ; Khathawatcharakun and Limsawasd, 2022 ), the sensitive circumstances of a pandemic require greater attention to maintaining the level of system functionality and minimizing the exposure to the risk of contact. This complex issue needs the development of a decision-support tool to suggest an effective train schedule that can concurrently reduce the unserved passengers and minimize passenger travel times during the sensitive pandemic case and its aftermath.…”