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Integrated optimization for train operation zone and stop plan with passenger distributions

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  • Qi, Jianguo
  • Yang, Lixing
  • Di, Zhen
  • Li, Shukai
  • Yang, Kai
  • Gao, Yuan

Abstract

With the aim of generating system-optimal operation strategies, this paper proposes a new integrated optimization method for train operation zone, stop plan and passenger distribution optimization problems on the basis of a train stop planning model. Through the introduction of a set of critical system constraints, the problem is rigorously formulated as a two-objective mixed-integer linear programming problem with the objectives of minimizing the total running distance of unoccupied seats and the total number of stops for all involved trains. Finally, two sets of numerical experiments are implemented using GAMS to demonstrate the performance of the proposed approach.

Suggested Citation

  • Qi, Jianguo & Yang, Lixing & Di, Zhen & Li, Shukai & Yang, Kai & Gao, Yuan, 2018. "Integrated optimization for train operation zone and stop plan with passenger distributions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 109(C), pages 151-173.
  • Handle: RePEc:eee:transe:v:109:y:2018:i:c:p:151-173
    DOI: 10.1016/j.tre.2017.11.003
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    1. Twan Dollevoet & Dennis Huisman & Marie Schmidt & Anita Schöbel, 2012. "Delay Management with Rerouting of Passengers," Transportation Science, INFORMS, vol. 46(1), pages 74-89, February.
    2. Zhan, Shuguang & Kroon, Leo G. & Zhao, Jun & Peng, Qiyuan, 2016. "A rolling horizon approach to the high speed train rescheduling problem in case of a partial segment blockage," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 95(C), pages 32-61.
    3. Zhou, Xuesong & Zhong, Ming, 2007. "Single-track train timetabling with guaranteed optimality: Branch-and-bound algorithms with enhanced lower bounds," Transportation Research Part B: Methodological, Elsevier, vol. 41(3), pages 320-341, March.
    4. Nielsen, Lars Kjær & Kroon, Leo & Maróti, Gábor, 2012. "A rolling horizon approach for disruption management of railway rolling stock," European Journal of Operational Research, Elsevier, vol. 220(2), pages 496-509.
    5. Gao, Yuan & Kroon, Leo & Schmidt, Marie & Yang, Lixing, 2016. "Rescheduling a metro line in an over-crowded situation after disruptions," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 425-449.
    6. Chang, Yu-Hern & Yeh, Chung-Hsing & Shen, Ching-Cheng, 2000. "A multiobjective model for passenger train services planning: application to Taiwan's high-speed rail line," Transportation Research Part B: Methodological, Elsevier, vol. 34(2), pages 91-106, February.
    7. Cacchiani, Valentina & Toth, Paolo, 2012. "Nominal and robust train timetabling problems," European Journal of Operational Research, Elsevier, vol. 219(3), pages 727-737.
    8. Haahr, Jørgen T. & Wagenaar, Joris C. & Veelenturf, Lucas P. & Kroon, Leo G., 2016. "A comparison of two exact methods for passenger railway rolling stock (re)scheduling," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 91(C), pages 15-32.
    9. Wang, Shuaian & Meng, Qiang & Yang, Hai, 2013. "Global optimization methods for the discrete network design problem," Transportation Research Part B: Methodological, Elsevier, vol. 50(C), pages 42-60.
    10. Corman, F. & D’Ariano, A. & Pacciarelli, D. & Pranzo, M., 2012. "Optimal inter-area coordination of train rescheduling decisions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(1), pages 71-88.
    11. Yin, Jiateng & Tang, Tao & Yang, Lixing & Gao, Ziyou & Ran, Bin, 2016. "Energy-efficient metro train rescheduling with uncertain time-variant passenger demands: An approximate dynamic programming approach," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 178-210.
    12. Fioole, Pieter-Jan & Kroon, Leo & Maroti, Gabor & Schrijver, Alexander, 2006. "A rolling stock circulation model for combining and splitting of passenger trains," European Journal of Operational Research, Elsevier, vol. 174(2), pages 1281-1297, October.
    13. Yang, Lixing & Qi, Jianguo & Li, Shukai & Gao, Yuan, 2016. "Collaborative optimization for train scheduling and train stop planning on high-speed railways," Omega, Elsevier, vol. 64(C), pages 57-76.
    14. D'Ariano, Andrea & Pacciarelli, Dario & Pranzo, Marco, 2007. "A branch and bound algorithm for scheduling trains in a railway network," European Journal of Operational Research, Elsevier, vol. 183(2), pages 643-657, December.
    15. Yang, Lixing & Zhou, Xuesong & Gao, Ziyou, 2014. "Credibility-based rescheduling model in a double-track railway network: a fuzzy reliable optimization approach," Omega, Elsevier, vol. 48(C), pages 75-93.
    16. Jan-Willem Goossens & Stan van Hoesel & Leo Kroon, 2004. "A Branch-and-Cut Approach for Solving Railway Line-Planning Problems," Transportation Science, INFORMS, vol. 38(3), pages 379-393, August.
    17. Yang, Xin & Chen, Anthony & Ning, Bin & Tang, Tao, 2017. "Bi-objective programming approach for solving the metro timetable optimization problem with dwell time uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 97(C), pages 22-37.
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    5. Hongguo Ren & Zhenbao Wang & Yanyan Chen, 2020. "Optimal Express Bus Routes Design with Limited-Stop Services for Long-Distance Commuters," Sustainability, MDPI, vol. 12(4), pages 1-14, February.
    6. Zhang, Yongxiang & Peng, Qiyuan & Yao, Yu & Zhang, Xin & Zhou, Xuesong, 2019. "Solving cyclic train timetabling problem through model reformulation: Extended time-space network construct and Alternating Direction Method of Multipliers methods," Transportation Research Part B: Methodological, Elsevier, vol. 128(C), pages 344-379.
    7. Nguyen, Hoa T.M. & Chow, Andy H.F. & Ying, Cheng-shuo, 2021. "Pareto routing and scheduling of dynamic urban rail transit services with multi-objective cross entropy method," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 156(C).
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    9. Xu, Guangming & Liu, Yihan & Gao, Yihan & Liu, Wei, 2023. "Integrated optimization of train stopping plan and seat allocation scheme for railway systems under equilibrium travel choice and elastic demand," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 177(C).
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