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Optimizing trains movement on a railway network

Author

Listed:
  • Yang, Lixing
  • Li, Keping
  • Gao, Ziyou
  • Li, Xiang

Abstract

Focusing on solving critically important train operation problems on a railway network, this paper investigates a mathematical model for finding optimal trains movements under the consideration of operational interactions. With the predetermined routing and traversing order plan, we explicitly consider the optimization of energy consumption and travel time as the objective based on the coasting control methods. To reduce the calculation difficulties, simulation-based methodologies are proposed to compute the energy consumption and traversing time through using specific performance of the involved trains. A genetic algorithm integrated with simulation is designed to seek the approximate optimal coasting control strategies on the railway network. The numerical experiments investigate the effectiveness of the proposed model and algorithm.

Suggested Citation

  • Yang, Lixing & Li, Keping & Gao, Ziyou & Li, Xiang, 2012. "Optimizing trains movement on a railway network," Omega, Elsevier, vol. 40(5), pages 619-633.
  • Handle: RePEc:eee:jomega:v:40:y:2012:i:5:p:619-633
    DOI: 10.1016/j.omega.2011.12.001
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    References listed on IDEAS

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    1. Blanco, Víctor & Puerto, Justo & Ramos, Ana B., 2011. "Expanding the Spanish high-speed railway network," Omega, Elsevier, vol. 39(2), pages 138-150, April.
    2. Qin, Zhongfeng & Ji, Xiaoyu, 2010. "Logistics network design for product recovery in fuzzy environment," European Journal of Operational Research, Elsevier, vol. 202(2), pages 479-490, April.
    3. Yu, Ming-Miin & Lin, Erwin T.J., 2008. "Efficiency and effectiveness in railway performance using a multi-activity network DEA model," Omega, Elsevier, vol. 36(6), pages 1005-1017, December.
    4. Hong, Sung-Pil & Kim, Kyung Min & Lee, Kyungsik & Hwan Park, Bum, 2009. "A pragmatic algorithm for the train-set routing: The case of Korea high-speed railway," Omega, Elsevier, vol. 37(3), pages 637-645, June.
    5. Kuo, Ching-Chung & Nicholls, Gillian M., 2007. "A mathematical modeling approach to improving locomotive utilization at a freight railroad," Omega, Elsevier, vol. 35(5), pages 472-485, October.
    6. He, Shiwei & Song, Rui & Chaudhry, Sohail S., 2000. "Fuzzy dispatching model and genetic algorithms for railyards operations," European Journal of Operational Research, Elsevier, vol. 124(2), pages 307-331, July.
    7. Liu, Rongfang (Rachel) & Golovitcher, Iakov M., 2003. "Energy-efficient operation of rail vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 37(10), pages 917-932, December.
    8. Chung, Ji-Won & Oh, Seog-Moon & Choi, In-Chan, 2009. "A hybrid genetic algorithm for train sequencing in the Korean railway," Omega, Elsevier, vol. 37(3), pages 555-565, June.
    9. Phil Howlett, 2000. "The Optimal Control of a Train," Annals of Operations Research, Springer, vol. 98(1), pages 65-87, December.
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    Citations

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    Cited by:

    1. Jaehn, Florian & Rieder, Johannes & Wiehl, Andreas, 2015. "Single-stage shunting minimizing weighted departure times," Omega, Elsevier, vol. 52(C), pages 133-141.
    2. Salazar-González, Juan-José, 2014. "Approaches to solve the fleet-assignment, aircraft-routing, crew-pairing and crew-rostering problems of a regional carrier," Omega, Elsevier, vol. 43(C), pages 71-82.
    3. repec:eee:transb:v:105:y:2017:i:c:p:340-361 is not listed on IDEAS
    4. Yaodong Ni & Zhaojun Zhao, 2017. "Two-agent scheduling problem under fuzzy environment," Journal of Intelligent Manufacturing, Springer, vol. 28(3), pages 739-748, March.
    5. Cacchiani, Valentina & Furini, Fabio & Kidd, Martin Philip, 2016. "Approaches to a real-world Train Timetabling Problem in a railway node," Omega, Elsevier, vol. 58(C), pages 97-110.
    6. Scheepmaker, Gerben M. & Goverde, Rob M.P. & Kroon, Leo G., 2017. "Review of energy-efficient train control and timetabling," European Journal of Operational Research, Elsevier, vol. 257(2), pages 355-376.
    7. repec:eee:energy:v:138:y:2017:i:c:p:1124-1147 is not listed on IDEAS
    8. 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.
    9. 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.
    10. Ye, Hongbo & Liu, Ronghui, 2016. "A multiphase optimal control method for multi-train control and scheduling on railway lines," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 377-393.
    11. 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.
    12. repec:eee:transe:v:109:y:2018:i:c:p:115-138 is not listed on IDEAS
    13. repec:eee:energy:v:151:y:2018:i:c:p:854-863 is not listed on IDEAS
    14. Wang, Li & Yang, Lixing & Gao, Ziyou, 2016. "The constrained shortest path problem with stochastic correlated link travel times," European Journal of Operational Research, Elsevier, vol. 255(1), pages 43-57.
    15. 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.

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