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Mathematical Problems in Engineering
Volume 2013, Article ID 805410, 12 pages
http://dx.doi.org/10.1155/2013/805410
Research Article

Simulation-Based Genetic Algorithm towards an Energy-Efficient Railway Traffic Control

1Department of Mathematics and Operational Research, University of Mons, 9 Rue de Houdain, B7000 Mons, Belgium
2School of Management, Shanghai University, No. 99 Shangda Road, Shanghai 200444, China

Received 11 October 2012; Revised 29 December 2012; Accepted 29 December 2012

Academic Editor: Wuhong Wang

Copyright © 2013 Daniel Tuyttens et al. 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.

Citations to this Article [9 citations]

The following is the list of published articles that have cited the current article.

  • Xiang Li, and Hong K. Lo, “An energy-efficient scheduling and speed control approach for metro rail operations,” Transportation Research Part B: Methodological, vol. 64, pp. 73–89, 2014. View at Publisher · View at Google Scholar
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  • Hyo Seon Park, Eunmi Kwon, Yousok Kim, and Se Woon Choi, “Resizing Technique-Based Hybrid Genetic Algorithm for Optimal Drift Design of Multistory Steel Frame Buildings,” Mathematical Problems in Engineering, vol. 2014, pp. 1–11, 2014. View at Publisher · View at Google Scholar
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  • Xin Yang, Anthony Chen, Bin Ning, and Tao Tang, “A stochastic model for the integrated optimization on metro timetable and speed profile with uncertain train mass,” Transportation Research Part B: Methodological, vol. 91, pp. 424–445, 2016. View at Publisher · View at Google Scholar
  • Pavel Masek, Jan Masek, Petr Frantik, Radek Fujdiak, Aleksandr Ometov, Jiri Hosek, Sergey Andreev, Petr Mlynek, and Jiri Misurec, “A Harmonized Perspective on Transportation Management in Smart Cities: The Novel IoT-Driven Environment for Road Traffic Modeling,” Sensors, vol. 16, no. 11, pp. 1872, 2016. View at Publisher · View at Google Scholar