IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v246y2015i3p772-786.html
   My bibliography  Save this article

High-speed railway scheduling based on user preferences

Author

Listed:
  • Espinosa-Aranda, José Luis
  • García-Ródenas, Ricardo
  • Ramírez-Flores, María del Carmen
  • López-García, María Luz
  • Angulo, Eusebio

Abstract

This paper proposes an optimization model for high-speed railway scheduling. The model is composed of two sub-models. The first is a discrete event simulation model which represents the supply of the railway services whereas the second is a constrained logit-type choice model which takes into account the behaviour of users. This discrete choice model evaluates the attributes of railway services such as the timetable, fare, travel time and seat availability (capacity constraints) and computes the High-Speed railway demand for each planned train service.

Suggested Citation

  • Espinosa-Aranda, José Luis & García-Ródenas, Ricardo & Ramírez-Flores, María del Carmen & López-García, María Luz & Angulo, Eusebio, 2015. "High-speed railway scheduling based on user preferences," European Journal of Operational Research, Elsevier, vol. 246(3), pages 772-786.
    • Handle: RePEc:eee:ejores:v:246:y:2015:i:3:p:772-786
    DOI: 10.1016/j.ejor.2015.05.052
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221715004634
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ejor.2015.05.052?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Benedikt Mandel & Marc Gaudry & Werner Rothengatter, 1997. "A disaggregate Box-Cox Logit mode choice model of intercity passenger travel in Germany and its implications for high-speed rail demand forecasts," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 31(2), pages 99-120.
    2. Román, Concepción & Espino, Raquel & Martín, Juan Carlos, 2007. "Competition of high-speed train with air transport: The case of Madrid–Barcelona," Journal of Air Transport Management, Elsevier, vol. 13(5), pages 277-284.
    3. Antonio Couto & Daniel Graham, 2008. "The impact of high-speed technology on railway demand," Transportation, Springer, vol. 35(1), pages 111-128, January.
    4. Corman, Francesco & D'Ariano, Andrea & Pacciarelli, Dario & Pranzo, Marco, 2010. "A tabu search algorithm for rerouting trains during rail operations," Transportation Research Part B: Methodological, Elsevier, vol. 44(1), pages 175-192, January.
    5. Cacchiani, Valentina & Toth, Paolo, 2012. "Nominal and robust train timetabling problems," European Journal of Operational Research, Elsevier, vol. 219(3), pages 727-737.
    6. Chaug-Ing Hsu & Wen-Ming Chung, 1997. "A model for market share distribution between high-speed and conventional rail services in a transportation corridor," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 31(2), pages 121-153.
    7. Yuanqing Wang & Lei Li & Li Wang & Adrian Moore & Samuel Staley & Zongzhi Li, 2014. "Modeling traveler mode choice behavior of a new high-speed rail corridor in China," Transportation Planning and Technology, Taylor & Francis Journals, vol. 37(5), pages 466-483, July.
    8. Jean-François Cordeau & Paolo Toth & Daniele Vigo, 1998. "A Survey of Optimization Models for Train Routing and Scheduling," Transportation Science, INFORMS, vol. 32(4), pages 380-404, November.
    9. Xiaowen Fu & Tae H. Oum & Jia Yan, 2014. "An Analysis of Travel Demand in Japan's Intercity Market Empirical Estimation and Policy Simulation," Journal of Transport Economics and Policy, University of Bath, vol. 48(1), pages 97-113, January.
    10. Wardman, Mark, 2006. "Demand for rail travel and the effects of external factors," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 42(3), pages 129-148, May.
    11. Yao, Enjian & Morikawa, Takayuki, 2005. "A study of on integrated intercity travel demand model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(4), pages 367-381, May.
    12. Juan Martín & Gustavo Nombela, 2007. "Microeconomic impacts of investments in high speed trains in Spain," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 41(3), pages 715-733, September.
    13. Anas, Alex, 1983. "Discrete choice theory, information theory and the multinomial logit and gravity models," Transportation Research Part B: Methodological, Elsevier, vol. 17(1), pages 13-23, February.
    14. Park, Yonghwa & Ha, Hun-Koo, 2006. "Analysis of the impact of high-speed railroad service on air transport demand," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 42(2), pages 95-104, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yin, Jiateng & D’Ariano, Andrea & Wang, Yihui & Yang, Lixing & Tang, Tao, 2021. "Timetable coordination in a rail transit network with time-dependent passenger demand," European Journal of Operational Research, Elsevier, vol. 295(1), pages 183-202.
    2. Maosheng Li & Qing Huang & Lixuan Yao & Yongliang Wang, 2020. "Suitability Evaluation of a Train’s Scheduled Section Travel Time," Sustainability, MDPI, vol. 12(6), pages 1-15, March.
    3. García-Ródenas, Ricardo & García-García, José Carlos & López-Fidalgo, Jesús & Martín-Baos, José Ángel & Wong, Weng Kee, 2020. "A comparison of general-purpose optimization algorithms for finding optimal approximate experimental designs," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).
    4. Robenek, Tomáš & Azadeh, Shadi Sharif & Maknoon, Yousef & de Lapparent, Matthieu & Bierlaire, Michel, 2018. "Train timetable design under elastic passenger demand," Transportation Research Part B: Methodological, Elsevier, vol. 111(C), pages 19-38.
    5. Xu, Guangming & Zhong, Linhuan & Liu, Wei & Guo, Jing, 2024. "A flexible train composition strategy with extra-long trains for high-speed railway corridors with time-varying demand," Transportation Research Part B: Methodological, Elsevier, vol. 179(C).
    6. José Luis Espinosa-Aranda & Ricardo García-Ródenas & María Luz López-García & Eusebio Angulo, 2018. "Constrained nested logit model: formulation and estimation," Transportation, Springer, vol. 45(5), pages 1523-1557, September.
    7. Meng, Lingyun & Zhou, Xuesong, 2019. "An integrated train service plan optimization model with variable demand: A team-based scheduling approach with dual cost information in a layered network," Transportation Research Part B: Methodological, Elsevier, vol. 125(C), pages 1-28.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cascetta, Ennio & Coppola, Pierluigi, 2016. "Assessment of schedule-based and frequency-based assignment models for strategic and operational planning of high-speed rail services," Transportation Research Part A: Policy and Practice, Elsevier, vol. 84(C), pages 93-108.
    2. Li, Zhi-Chun & Sheng, Dian, 2016. "Forecasting passenger travel demand for air and high-speed rail integration service: A case study of Beijing-Guangzhou corridor, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 397-410.
    3. Asep Yayat Nurhidayat & Hera Widyastuti & Sutikno & Dwi Phalita Upahita, 2023. "Research on Passengers’ Preferences and Impact of High-Speed Rail on Air Transport Demand," Sustainability, MDPI, vol. 15(4), pages 1-26, February.
    4. Zhang, Anming & Wan, Yulai & Yang, Hangjun, 2019. "Impacts of high-speed rail on airlines, airports and regional economies: A survey of recent research," Transport Policy, Elsevier, vol. 81(C), pages 1-19.
    5. Pellegrini, Paola & Rodriguez, Joaquin, 2013. "Single European Sky and Single European Railway Area: A system level analysis of air and rail transportation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 57(C), pages 64-86.
    6. Tsunoda, Yushi, 2018. "Transportation policy for high-speed rail competing with airlines," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 350-360.
    7. Isler, Cassiano Augusto & Blumenfeld, Marcelo & Caldeira, Gabriel Pereira & Roberts, Clive, 2024. "Long-Distance railway mode choice in Brazil: Evidence from a discrete choice experiment," Research in Transportation Economics, Elsevier, vol. 104(C).
    8. Xiaomei Lin & Yusak O. Susilo & Chunfu Shao & Chengxi Liu, 2018. "The Implication of Road Toll Discount for Mode Choice: Intercity Travel during the Chinese Spring Festival Holiday," Sustainability, MDPI, vol. 10(8), pages 1-16, August.
    9. Albalate, Daniel & Bel, Germà & Fageda, Xavier, 2015. "Competition and cooperation between high-speed rail and air transportation services in Europe," Journal of Transport Geography, Elsevier, vol. 42(C), pages 166-174.
    10. Yin, Jiateng & Yang, Lixing & Tang, Tao & Gao, Ziyou & Ran, Bin, 2017. "Dynamic passenger demand oriented metro train scheduling with energy-efficiency and waiting time minimization: Mixed-integer linear programming approaches," Transportation Research Part B: Methodological, Elsevier, vol. 97(C), pages 182-213.
    11. Zhou, Leishan & Tong, Lu (Carol) & Chen, Junhua & Tang, Jinjin & Zhou, Xuesong, 2017. "Joint optimization of high-speed train timetables and speed profiles: A unified modeling approach using space-time-speed grid networks," Transportation Research Part B: Methodological, Elsevier, vol. 97(C), pages 157-181.
    12. Hu, Xinlei & Wang, Xiaokun (Cara) & Ni, Linglin & Shi, Feng, 2022. "The impact of intercity economic complementarity on HSR volume in the context of megalopolization," Journal of Transport Geography, Elsevier, vol. 98(C).
    13. Li, Zhi-Chun & Tu, Ningwen & Fu, Xiaowen & Sheng, Dian, 2022. "Modeling the effects of airline and high-speed rail cooperation on multi-airport systems: The implications on congestion, competition and social welfare," Transportation Research Part B: Methodological, Elsevier, vol. 155(C), pages 448-478.
    14. Meng, Xuechen & Lin, Shanlang & Zhu, Xiaochuan, 2018. "The resource redistribution effect of high-speed rail stations on the economic growth of neighbouring regions: Evidence from China," Transport Policy, Elsevier, vol. 68(C), pages 178-191.
    15. Albalate, Daniel & Fageda, Xavier, 2016. "High speed rail and tourism: Empirical evidence from Spain," Transportation Research Part A: Policy and Practice, Elsevier, vol. 85(C), pages 174-185.
    16. Xiaoming Xu & Keping Li & Lixing Yang & Ziyou Gao, 2019. "An efficient train scheduling algorithm on a single-track railway system," Journal of Scheduling, Springer, vol. 22(1), pages 85-105, February.
    17. Adler, Nicole & Pels, Eric & Nash, Chris, 2010. "High-speed rail and air transport competition: Game engineering as tool for cost-benefit analysis," Transportation Research Part B: Methodological, Elsevier, vol. 44(7), pages 812-833, August.
    18. Dobruszkes, Frédéric, 2011. "High-speed rail and air transport competition in Western Europe: A supply-oriented perspective," Transport Policy, Elsevier, vol. 18(6), pages 870-879, November.
    19. Wan, Yulai & Ha, Hun-Koo & Yoshida, Yuichiro & Zhang, Anming, 2016. "Airlines’ reaction to high-speed rail entries: Empirical study of the Northeast Asian market," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 532-557.
    20. Min Su & Weixin Luan & Liuyan Yuan & Rui Zhang & Zhenchao Zhang, 2019. "Sustainability Development of High-Speed Rail and Airline—Understanding Passengers’ Preferences: A Case Study of the Beijing–Shanghai Corridor," Sustainability, MDPI, vol. 11(5), pages 1-19, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:246:y:2015:i:3:p:772-786. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.