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Timetable optimization models and methods for minimizing passenger waiting time at public transit terminals

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  • Erfan Hassannayebi
  • Seyed Hessameddin Zegordi
  • Masoud Yaghini
  • Mohammad Reza Amin-Naseri

Abstract

This paper focuses on developing mathematical optimization models for the train timetabling problem with respect to dynamic travel demand and capacity constraints. The train scheduling models presented in this paper aim to minimize passenger waiting times at public transit terminals. Linear and non-linear formulations of the problem are presented. The non-linear formulation is then improved through introducing service frequency variables. Heuristic rules are suggested and embedded in the improved non-linear formulation to reduce the computational time effort needed to find the upper bound. The effectiveness of the proposed train timetabling models is illustrated through the application to an underground urban rail line in the city of Tehran. The results demonstrate the effectiveness of the proposed demand-oriented train timetabling models, in terms of decreasing passenger waiting times. Compared to the baseline and regular timetables, total waiting time is reduced by 6.36% and 10.55% respectively, through the proposed mathematical optimization models.

Suggested Citation

  • Erfan Hassannayebi & Seyed Hessameddin Zegordi & Masoud Yaghini & Mohammad Reza Amin-Naseri, 2017. "Timetable optimization models and methods for minimizing passenger waiting time at public transit terminals," Transportation Planning and Technology, Taylor & Francis Journals, vol. 40(3), pages 278-304, April.
    • Handle: RePEc:taf:transp:v:40:y:2017:i:3:p:278-304
    DOI: 10.1080/03081060.2017.1283156
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    References listed on IDEAS

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    1. Jack P. C. Kleijnen, 2015. "Response Surface Methodology," International Series in Operations Research & Management Science, in: Michael C Fu (ed.), Handbook of Simulation Optimization, edition 127, chapter 0, pages 81-104, Springer.
    2. Mohammad Reza Amin-Naseri & Vahid Baradaran, 2015. "Accurate Estimation of Average Waiting Time in Public Transportation Systems," Transportation Science, INFORMS, vol. 49(2), pages 213-222, May.
    3. Jack P. C. Kleijnen, 2015. "Response Surface Methodology," International Series in Operations Research & Management Science, in: Michael C Fu (ed.), Handbook of Simulation Optimization, edition 127, chapter 0, pages 81-104, Springer.
    4. Eberlein, Xu Jun & Wilson, Nigel H. M. & Barnhart, Cynthia & Bernstein, David, 1998. "The real-time deadheading problem in transit operations control," Transportation Research Part B: Methodological, Elsevier, vol. 32(2), pages 77-100, February.
    5. Barrena, Eva & Canca, David & Coelho, Leandro C. & Laporte, Gilbert, 2014. "Single-line rail rapid transit timetabling under dynamic passenger demand," Transportation Research Part B: Methodological, Elsevier, vol. 70(C), pages 134-150.
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    Cited by:

    1. M. Shakibayifar & A. Sheikholeslami & F. Corman & E. Hassannayebi, 2020. "An integrated rescheduling model for minimizing train delays in the case of line blockage," Operational Research, Springer, vol. 20(1), pages 59-87, March.
    2. Mitra Heidari & Seyyed-Mahdi Hosseini-Motlagh & Nariman Nikoo, 2020. "A subway planning bi-objective multi-period optimization model integrating timetabling and vehicle scheduling: a case study of Tehran," Transportation, Springer, vol. 47(1), pages 417-443, February.
    3. Han, Zhenyu & Han, Baoming & Li, Dewei & Ning, Shangbin & Yang, Ruixia & Yin, Yonghao, 2021. "Train timetabling in rail transit network under uncertain and dynamic demand using Advanced and Adaptive NSGA-II," Transportation Research Part B: Methodological, Elsevier, vol. 154(C), pages 65-99.

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