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Journal of Applied Mathematics
Volume 2014, Article ID 507308, 7 pages
Research Article

Optimization of High-Speed Train Control Strategy for Traction Energy Saving Using an Improved Genetic Algorithm

1College of Information Science and Engineering, Northeastern University, Shenyang 110004, China
2Service Science Research Center, Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201203, China

Received 27 March 2014; Accepted 9 April 2014; Published 4 May 2014

Academic Editor: Young-Sik Jeong

Copyright © 2014 Ruidan Su 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 [8 citations]

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

  • Rui Zhou, and Shiji Song, “Optimal automatic train operation via deep reinforcement learning,” 2018 Tenth International Conference on Advanced Computational Intelligence (ICACI), pp. 103–108, . View at Publisher · View at Google Scholar
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  • Xiaojie Luan, Yihui Wang, Bart De Schutter, Lingyun Meng, Gabriel Lodewijks, and Francesco Corman, “Integration of real-time traffic management and train control for rail networks - Part 2: Extensions towards energy-efficient train operations,” Transportation Research Part B: Methodological, vol. 115, pp. 72–94, 2018. View at Publisher · View at Google Scholar