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Discrete Dynamics in Nature and Society
Volume 2012 (2012), Article ID 549374, 13 pages
An Optimization to Schedule Train Operations with Phase-Regular Framework for Intercity Rail Lines
School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou 730070, China
Received 7 September 2012; Accepted 15 October 2012
Academic Editor: Wuhong Wang
Copyright © 2012 Huimin Niu and Minghui Zhang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- N. S. A. Ghoneim and S. C. Wirasinghe, “Optimum zone structure during peak periods for existing urban rail lines,” Transportation Research B, vol. 20, no. 1, pp. 7–18, 1986.
- J. W. Goossens, S. van Hoesel, and L. Kroon, “On solving multi-type railway line planning problems,” European Journal of Operational Research, vol. 168, no. 2, pp. 403–424, 2006.
- C. Liebchen, “The first optimized railway timetable in practice,” Transportation Science, vol. 42, no. 4, pp. 420–435, 2008.
- M. T. Claessens, N. M. Van Dijk, and P. J. Zwaneveld, “Cost optimal allocation of rail passenger lines,” European Journal of Operational Research, vol. 110, no. 3, pp. 474–489, 1998.
- K. Ghoseiri, F. Szidarovszky, and M. J. Asgharpour, “A multi-objective train scheduling model and solution,” Transportation Research B, vol. 38, no. 10, pp. 927–952, 2004.
- M. B. Khan and X. Zhou, “Stochastic optimization model and solution algorithm for robust double-track train-timetabling problem,” IEEE Transactions on Intelligent Transportation Systems, vol. 11, no. 1, pp. 81–89, 2010.
- X. Zhou and M. Zhong, “Single-track train timetabling with guaranteed optimality: branch-and-bound algorithms with enhanced lower bounds,” Transportation Research B, vol. 41, no. 3, pp. 320–341, 2007.
- K. Nachtigall and S. Voget, “Minimizing waiting times in integrated fixed interval timetables by upgrading railway tracks,” European Journal of Operational Research, vol. 103, no. 3, pp. 610–627, 1997.
- A. de Palma and R. Lindsey, “Optimal timetables for public transportation,” Transportation Research B, vol. 35, no. 8, pp. 789–813, 2001.
- S. Nguyen, S. Pallottino, and F. Malucelli, “A modeling framework for passenger assignment on a transport network with timetables,” Transportation Science, vol. 35, no. 3, pp. 238–249, 2001.
- R. C. W. Wong, T. W. Y. Yuen, K. W. Fung, and J. M. Y. Leung, “Optimizing timetable synchronization for rail mass transit,” Transportation Science, vol. 42, no. 1, pp. 57–69, 2008.
- L. Meng and X. Zhou, “Robust single-track train dispatching model under a dynamic and stochastic environment: a scenario-based rolling horizon solution approach,” Transportation Research B, vol. 45, no. 7, pp. 1080–1102, 2011.
- M. Carey and I. Crawford, “Scheduling trains on a network of busy complex stations,” Transportation Research B, vol. 41, no. 2, pp. 159–178, 2007.
- G. Caimi, F. Chudak, M. Fuchsberger, M. Laumanns, and R. Zenklusen, “A new resource-constrained multicommodity flow model for conflict-free train routing and scheduling,” Transportation Science, vol. 45, no. 2, pp. 212–227, 2011.
- Y. H. Chang, C. H. Yeh, and C. C. Shen, “A multiobjective model for passenger train services planning: application to Taiwan's high-speed rail line,” Transportation Research B, vol. 34, no. 2, pp. 91–106, 2000.
- M. Gen and R. W. Cheng, Genetic Algorithms and Engineering Optimization, John Wiley & Son, New York, NY, USA, 2000.
- H. M. Niu, “Determination of the skip-stop scheduling for a congested transit line by bilevel genetic algorithm,” International Journal of Computational Intelligence Systems, vol. 4, no. 6, pp. 1158–1167, 2011.
- J. Gao,, R. Chen, and Q. Pan, “A hybrid genetic algorithm for the distributed permutation flowshop scheduling problem,” International Journal of Computational Intelligence Systems, vol. 4, no. 4, pp. 497–508, 2011.