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A practical model for transfer optimization in a transit network: Model formulations and solutions

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  • Shafahi, Yousef
  • Khani, Alireza

Abstract

This paper studies the transit network scheduling problem and aims to minimize the waiting time at transfer stations. First, the problem is formulated as a mixed integer programming model that gives the departure times of vehicles in lines so that passengers can transfer between lines at transfer stations with minimum waiting times. Then, the model is expanded to a second model by considering the extra stopping time of vehicles at transfer stations as a new variable set. By calculating the optimal values for these variables, transfers can be better performed. The sizes of the models, compared with the existing models, are small enough that the models can be solved for small- and medium-sized networks using regular MIP solvers, such as CPLEX. Moreover, a genetic algorithm approach is represented to more easily solve larger networks. A simple network is used to describe the models, and a medium-sized, real-life network is used to compare the proposed models with another existing model in the literature. The results demonstrate significant improvement. Finally, a large-scale, real-life network is used as a case study to evaluate the proposed models and the genetic algorithm approach.

Suggested Citation

  • Shafahi, Yousef & Khani, Alireza, 2010. "A practical model for transfer optimization in a transit network: Model formulations and solutions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(6), pages 377-389, July.
  • Handle: RePEc:eee:transa:v:44:y:2010:i:6:p:377-389
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    References listed on IDEAS

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    1. Zhao, Fang & Zeng, Xiaogang, 2008. "Optimization of transit route network, vehicle headways and timetables for large-scale transit networks," European Journal of Operational Research, Elsevier, vol. 186(2), pages 841-855, April.
    2. Yan, Shangyao & Chi, Chin-Jen & Tang, Ching-Hui, 2006. "Inter-city bus routing and timetable setting under stochastic demands," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(7), pages 572-586, August.
    3. Haghani, Ali & Shafahi, Yousef, 2002. "Bus maintenance systems and maintenance scheduling: model formulations and solutions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 36(5), pages 453-482, June.
    4. Castelli, Lorenzo & Pesenti, Raffaele & Ukovich, Walter, 2004. "Scheduling multimodal transportation systems," European Journal of Operational Research, Elsevier, vol. 155(3), pages 603-615, June.
    5. Haghani, Ali & Banihashemi, Mohamadreza & Chiang, Kun-Hung, 2003. "A comparative analysis of bus transit vehicle scheduling models," Transportation Research Part B: Methodological, Elsevier, vol. 37(4), pages 301-322, May.
    6. Yan, Shangyao & Chen, Hao-Lei, 2002. "A scheduling model and a solution algorithm for inter-city bus carriers," Transportation Research Part A: Policy and Practice, Elsevier, vol. 36(9), pages 805-825, November.
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    Citations

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    Cited by:

    1. Cinzia Daraio & Marco Diana & Flavia Di Costa & Claudio Leporelli & Giorgio Matteucci & Alberto Nastasi, 2014. "Efficiency and effectiveness in the urban public transport sector: a critical review with directions for future research," DIAG Technical Reports 2014-14, Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza".
    2. Guo, Xin & Sun, Huijun & Wu, Jianjun & Jin, Jiangang & Zhou, Jin & Gao, Ziyou, 2017. "Multiperiod-based timetable optimization for metro transit networks," Transportation Research Part B: Methodological, Elsevier, vol. 96(C), pages 46-67.
    3. repec:eee:trapol:v:66:y:2018:i:c:p:40-48 is not listed on IDEAS
    4. Kang, Liujiang & Zhu, Xiaoning & Sun, Huijun & Puchinger, Jakob & Ruthmair, Mario & Hu, Bin, 2016. "Modeling the first train timetabling problem with minimal missed trains and synchronization time differences in subway networks," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 17-36.
    5. Kang, Liujiang & Wu, Jianjun & Sun, Huijun & Zhu, Xiaoning & Gao, Ziyou, 2015. "A case study on the coordination of last trains for the Beijing subway network," Transportation Research Part B: Methodological, Elsevier, vol. 72(C), pages 112-127.
    6. Kang, Liujiang & Wu, Jianjun & Sun, Huijun & Zhu, Xiaoning & Wang, Bo, 2015. "A practical model for last train rescheduling with train delay in urban railway transit networks," Omega, Elsevier, vol. 50(C), pages 29-42.
    7. Guo, Zhan & Wilson, Nigel H.M., 2011. "Assessing the cost of transfer inconvenience in public transport systems: A case study of the London Underground," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(2), pages 91-104, February.
    8. repec:eee:trapol:v:59:y:2017:i:c:p:134-141 is not listed on IDEAS
    9. Daraio, Cinzia & Diana, Marco & Di Costa, Flavia & Leporelli, Claudio & Matteucci, Giorgio & Nastasi, Alberto, 2016. "Efficiency and effectiveness in the urban public transport sector: A critical review with directions for future research," European Journal of Operational Research, Elsevier, vol. 248(1), pages 1-20.
    10. repec:eee:transb:v:109:y:2018:i:c:p:128-149 is not listed on IDEAS
    11. Yang, Lixing & Zhang, Yan & Li, Shukai & Gao, Yuan, 2016. "A two-stage stochastic optimization model for the transfer activity choice in metro networks," Transportation Research Part B: Methodological, Elsevier, vol. 83(C), pages 271-297.
    12. Pternea, Moschoula & Kepaptsoglou, Konstantinos & Karlaftis, Matthew G., 2015. "Sustainable urban transit network design," Transportation Research Part A: Policy and Practice, Elsevier, vol. 77(C), pages 276-291.

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