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Demand-Oriented Train Timetabling Integrated with Passenger Train-Booking Decisions

Author

Listed:
  • Wenliang Zhou

    (School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China)

  • Wenzhuang Fan

    (School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China)

  • Xiaorong You

    (School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China)

  • Lianbo Deng

    (School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China)

Abstract

In recent years, with the global energy shortage and severe environmental deterioration, railway transport has begun to attract great interest as a green transportation mode. One of the vital means to realize social sustainable development is to improve railway transportation systems, in which providing a demand-oriented train timetable with a higher service level is the most viable method. A demand-oriented train timetable problem generally deals with passengers’ train-choice decisions according to the queue principle, but it is not adapted to rail systems, such as China’s, where passengers usually book tickets a few days in advance by telephone or online instead of going to stations. This paper is devoted to modeling and solving the demand-oriented train timetabling problem integrated with passengers’ train-booking decisions. Firstly, a bi-level programming model is formulated for their integrated optimization on a rail network. Its upper-level model is to optimize train arrival and departure times at each visited station with the aim of reducing passengers’ total travel cost, while its lower-level model aims to determine passengers’ train-booking behavior using the user equilibrium theory. Then, a priority-based heuristic algorithm is designed to solve this model. It has two main steps at each iteration: one is to determine the number of passengers booking each train with a given train timetable, and the other is to improve the current train timetable based on the valuable information of passenger train-booking decisions. The performance, convergence, and practicability of the proposed method were analyzed based on the Changsha–Zhuzhou–Xiangtan intercity rail in China. Experimental results show the proposed method can effectively reduce the travel cost for passengers, creating a greater passenger demand for railway travel, which is beneficial to the sustainable development of railway systems and even society.

Suggested Citation

  • Wenliang Zhou & Wenzhuang Fan & Xiaorong You & Lianbo Deng, 2019. "Demand-Oriented Train Timetabling Integrated with Passenger Train-Booking Decisions," Sustainability, MDPI, vol. 11(18), pages 1-34, September.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:18:p:4932-:d:265719
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    2. Yidong Wang & Rui Song & Shiwei He & Zilong Song, 2022. "Train Routing and Track Allocation Optimization Model of Multi-Station High-Speed Railway Hub," Sustainability, MDPI, vol. 14(12), pages 1-21, June.
    3. Manuel Blanco-Castillo & Adrián Fernández-Rodríguez & Antonio Fernández-Cardador & Asunción P. Cucala, 2022. "Eco-Driving in Railway Lines Considering the Uncertainty Associated with Climatological Conditions," Sustainability, MDPI, vol. 14(14), pages 1-26, July.
    4. Martin-Iradi, Bernardo & Ropke, Stefan, 2022. "A column-generation-based matheuristic for periodic and symmetric train timetabling with integrated passenger routing," European Journal of Operational Research, Elsevier, vol. 297(2), pages 511-531.
    5. Gonzalo Sánchez-Contreras & Adrián Fernández-Rodríguez & Antonio Fernández-Cardador & Asunción P. Cucala, 2023. "A Two-Level Fuzzy Multi-Objective Design of ATO Driving Commands for Energy-Efficient Operation of Metropolitan Railway Lines," Sustainability, MDPI, vol. 15(12), pages 1-24, June.

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