Abstract
As an important means of transportation, urban rail transit provides effective mobility, sufficient punctuality, strong security, and environment-friendliness in large cities. However, this transportation mode cannot offer a 24-h service to passengers with the consideration of operation cost and the necessity of maintenance, that is, a final time should be set. Therefore, operators need to design a last train timetable in consideration of the number of successful travel passengers and the total passenger transfer waiting time. This paper proposes a bi-level last train timetable optimization model. Its upper level model aims to maximize the number of passengers who travel by the last train service successful and minimize their transfer waiting time, and its lower level model aims to determine passenger route choice considering the detour routing strategy based on the last train timetable. A genetic algorithm is proposed to solve the upper level model, and the lower level model is solved by a semi-assignment algorithm. The implementation of the proposed model in the Beijing urban rail transit network proves that the model can optimize not only the number of successful transfer directions and successful travel passengers but also the passenger transfer waiting time of successful transfer directions. The optimization results can provide operators detailed information about the stations inaccessible to passengers from all origin stations and uncommon path guides for passengers of all origin–destination pairs. These types of information facilitate the operation of real-world urban rail transit systems.
Highlights
Motivation and incitementWith the continuous expansion of urban traffic demand, the urban rail transit plays an increasingly important role in the urban public transport system because of its effective mobility, sufficient punctuality, strong security, and environment-friendliness.1–3 As one of the most important stages in operation management, the timetable has a significant effect on the quality and efficiency of urban rail transit systems
This study belongs to a special class of urban railway train timetable optimization problem (TTP), namely the last train timetable optimization problem (LTTP)
Maximize connection headway Minimize the running and the dwell times and the difference between the original and the rescheduled timetable, maximize the average transfer redundant time Minimize total transfer connection time Maximize the social service efficiency and minimize the revenue loss for the operating companies Minimize the number of failed passengers for last train service and the transfer waiting time for first train service Maximize the number of successful travel passengers, minimize the transfer waiting time
Summary
With the continuous expansion of urban traffic demand, the urban rail transit plays an increasingly important role in the urban public transport system because of its effective mobility, sufficient punctuality, strong security, and environment-friendliness. As one of the most important stages in operation management, the timetable has a significant effect on the quality and efficiency of urban rail transit systems. Their transfer waiting time, while the OD-based passenger demand and the detour routing strategy are mainly considered for the particular last train services in an urban rail transit network. Besides the detour routing strategy, the origin– destination (OD) based passenger demand should be considered to assess the network accessibility for the last train service.9,10 This is because the independent transfer optimization cannot guarantee that most of the passengers can complete their travel through the last train service under network operation. We aim to propose a last train timetable optimization model in this study to maximize the number of successful travel passengers and minimize
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
