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Optimizing trains movement on a railway network

Listed author(s):
  • Yang, Lixing
  • Li, Keping
  • Gao, Ziyou
  • Li, Xiang
Registered author(s):

    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.

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    Article provided by Elsevier in its journal Omega.

    Volume (Year): 40 (2012)
    Issue (Month): 5 ()
    Pages: 619-633

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    Handle: RePEc:eee:jomega:v:40:y:2012:i:5:p:619-633
    DOI: 10.1016/
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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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