Open Access
Issue
E3S Web of Conf.
Volume 458, 2023
International Scientific Conference Energy Management of Municipal Facilities and Environmental Technologies (EMMFT-2023)
Article Number 10025
Number of page(s) 11
Section Energy Engineering and Mechanical Engineering
DOI https://doi.org/10.1051/e3sconf/202345810025
Published online 07 December 2023
  1. A. Grünig, Efficient Generation of Train Speed Profiles, Bachelor’s Thesis, Institute for Operations Research, ETH Zurich, 2009. [Google Scholar]
  2. C. Chang and S. Sim, “Optimising train movements through coast control using genetic algorithms,” IEE Proceedings - Electric Power Applications, vol. 144, no. 1, pp. 65–73, Jan. 1997. [CrossRef] [Google Scholar]
  3. Golovitcher, I. M. (2001). “Energy efficient control of rail vehicles. Systems, man, and cybernetics.” Proc., IEEE Int. Conf., Vol. 1, Tucson, AZ, pp. 658–663. [Google Scholar]
  4. H. Ko, T. Koseki, and M. Miyatake, “Application of dynamic programming to optimization of running profile of a train,” in Computers in Railways IX, WIT Press, vol. 15, Southampton, Boston, Sept. 2004, pp. 103–112. [Google Scholar]
  5. K. Ichikawa, “Application of optimization theory for bounded state variable problems to the operation of a train,” Bulletin of Japanese Society of Mechanical Engineering, vol. 11, no. 47, pp. 857–865, Nov. 1968. [CrossRef] [Google Scholar]
  6. M. Miyatake and H. Ko, “Optimization of train speed profile for minimum energy consumption,” IEEE Transactions on Electrical and Electronic Engineering, vol. 5, no. 3, pp. 263–269, May 2010. [CrossRef] [Google Scholar]
  7. Nilam R. Dongre. “Optimization of Energy Consumption In Electric Traction System By Using Interior Point Method.” IOSR Journal of Electrical and Electronics Engineering (IOSRJEEE) 13.2 (2018): pp. 9–15. [Google Scholar]
  8. P. G. Howlett, “Existence of an Optimal Strategy for the Control of a Train,” South Australian Inst. Technol., School Math. Rep., Adelaide, SA, Australia, 1987. [Google Scholar]
  9. P. G. Howlett, “Necessary conditions on an optimal strategy for the control of a train,” South Australian Inst. Technol., School Math. Rep., Adelaide, SA, Australia, 1987. [Google Scholar]
  10. P. Howlett, “The optimal control of a train,” Annals of Operations Research, vol. 98, no. 1–4, pp. 65–87, Dec. 2000. [CrossRef] [Google Scholar]
  11. P. Kokotovic and G. Singh, “Minimum-energy control of a traction motor,” IEEE Trans. Autom. Control, vol. 17, no. 1, pp. 92–95, Feb. 1972. [CrossRef] [Google Scholar]
  12. Peter Horn. Uber die Anwendung des MaximumPrinzips von Pontrjagin zur Ermittlung von Algorithmen fur eine energieoptimale Zugsteuerung. Wassenschaftliche Zeitschrift der Hochschule fur Verkehrswesen “Fhedrich List” in Dresden, 18(4), 1971. [Google Scholar]
  13. R. Franke, M. Meyer, and P. Terwiesch, “Optimal control of the driving of trains,” Automatisierungstechnik, vol. 50, no. 12, pp. 606–614, Dec. 2002. [CrossRef] [Google Scholar]
  14. R. Liu and I. M. Golovicher, “Energy-efficient operation of rail vehicles,” Transportation Research Part A: Policy and Practice, vol. 37, no. 10, pp. 917–931, Oct. 2003. [CrossRef] [Google Scholar]
  15. S. H. Han, Y. S. Byen, J. H. Baek, T. K. An, S. G. Lee, and H. J. Park, “An optimal automatic train operation (ATO) control using genetic algorithms (GA),” in Proceedings of the IEEE Region 10 Conference (TENCON 99), vol. 1, Korea, Aug. 1999, pp. 360–362. [Google Scholar]
  16. S. Su, T. Tang, C. Roberts, and L. Huang, “Cooperative train control for energy-saving,” in Proc. IEEE Int. Conf. Intell. Rail Transp., Beijing, China, Aug. 2013, pp. 7–12. [Google Scholar]
  17. S. Yasunobu, S. Miyamoto, and H. Ihara, “Fuzzy control for automatic train operation system,” in Proceedings of 4th IFAC/IFIP/IFORS International Conference on Control in Transportation Systems, Baden, Germany, June 1983, pp. 39–45. [Google Scholar]
  18. Y. V. Bocharnikov, A. M. Tobias, and C. Roberts, “Reduction of train and net energy consumption using genetic algorithms for trajectory optimization,” in Proc. IET Conf. Railway Traction Syst., Birmingham, U.K., Apr. 2010, pp. 32–36. [Google Scholar]
  19. Y. Bocharnikov, A. Tobias, C. Roberts, S. Hillmansen, and C. Goodman, “Optimal driving strategy for traction energy saving on dc suburban railways,” IEE Proceedings - Electric Power Applications, vol. 1, no. 5, pp. 675–682, Sept. 2007. [CrossRef] [Google Scholar]
  20. R. Chen, L. Liu and J. Guo, “Optimization of High-Speed Train Control Strategy for Traction Energy Saving Using an Improved Genetic Algorithm”, Journal of Traffic and Transportation Engineering. 1, 12 (2012). [Google Scholar]
  21. S. Sun, Y. Li and H. Xu, “Energy Consumption Optimization for High-speed Railway based on Particle Swarm Algorithm”, Proceedings of 4th International Conference on Computational Intelligence and Communication Networks, (2012) November 3–5; Mathura, India. [Google Scholar]
  22. S. Su, X. Li, T. Tang, and Z. Gao, “A subway train timetable optimization approach based on energy-efficient operation strategy,” IEEE Trans. Intell. Transp. Syst., vol. 14, no. 2, pp. 883–893, Jun. 2013. [CrossRef] [Google Scholar]
  23. X. Li and H. K. Lo, “An energy-efficient scheduling and speed control approach for metro rail operations,” Transp. Res. Part B.: Methodol., vol. 64, pp. 73–89, Jun. 2014. [CrossRef] [Google Scholar]
  24. X. Yang, X. Li, B. Ning, and T. Tang, “An optimization method for train scheduling with minimum energy consumption and travel Time in metro rail systems,” Transportmetrica B: Transp. Dyn., vol. 3, no. 2, pp. 79–98, 2015. [CrossRef] [Google Scholar]
  25. X. Yang, X. Li, Z. Gao, H. Wang, and T. Tang, “A cooperative scheduling model for timetable optimization in subway systems,” IEEE Trans. Intell. Transp. Syst., vol. 14, no. 1, pp. 438–447, Mar. 2013. [CrossRef] [Google Scholar]
  26. C. Chang and D. Xu, “Differential evolution based tuning of fuzzy automatic train operation for mass rapid transit system,” IEE Proceedings – Electric Power Applications, vol. 147, no. 3, pp. 206–212, May 2000. [CrossRef] [Google Scholar]
  27. K. K. Wong and T. K. Ho, “Dwell-time and run-time control for DC mass rapid transit railways,” Proc. Inst. Elect. Eng.—Elect. Power Appl., vol. 6, no. 1, pp. 956–966, Nov. 2007. [Google Scholar]
  28. S. Acikbas and M. Soylemez, “Coasting point optimization for mass rail transit lines using artifical neural networks and genetic algorithms,” Proceedings of the IEE Proceedings - Electric Power Applications, vol. 2, no. 3, pp. 172–182, May 2008. [Google Scholar]
  29. Y. Ding, H. Liu, Y. Bai, and F. Zhou, “A two-level optimization model and algorithm for energy-efficient urban train operation,” J. Transp. Syst. Eng. Inf. Technol., vol. 11, no. 1, pp. 96–101, Feb. 2011. [Google Scholar]
  30. Kostromin A. M. Optimization of locomotive management, Moscow, Transport, 1979, 119 p (In Russian). [Google Scholar]
  31. Klimovich A. V. Optimization of train movement control to minimize the cost of energy resources for traction, Moscow, Sputnik+ company, 2008, 263 p. (In Russian). [Google Scholar]
  32. Yurenko K. I. Calculation of energy-optimal modes of movement of promising rolling stock by dynamic programming method. Bulletin of universities. electromechanics, 2013, no.3, pp.78-82 (In Russian). [Google Scholar]
  33. Lesov A. T. Analysis of methods for solving problems of optimal control of train movement. // Electronics and electrical equipment of transport. – Tomilinsky Electronic Plant, 2022, issue. 3. – pp. 23–29. [Google Scholar]
  34. Bellman R. Dynamic programming / R. Bellman - M.: Foreign literature, 1960, 400 p. [Google Scholar]
  35. Bellman R. Applied problems of dynamic programming (translation from English Lurie K. A.) / R. Bellman, S. Dreyfus. - M.: Nauka, 1965, 460 p. [Google Scholar]
  36. Pontryagin L. S., Boltyanskij V. G., Gamkrelidze R. V., Mishchenko E. F. Mathematical theory of optimal processes, Moscow, Nauka Publ., 1983, 392 p (In Russian). [Google Scholar]
  37. Pontryagin L. S. The principle of maximum in optimal control, Moscow, Nauka Publ., 1989, 62 p (In Russian). [Google Scholar]
  38. Ablyalimov, O. S. Optimization of locomotive transportation work: theoretical issues, methods, calculations, results. / O. S. Ablyalimov. – Text: direct // Monograph / Tashkent Institute of Railway Transport Engineers. – Tashkent: “Complex Print” nashriyoti, 2020. – 488 p. [Google Scholar]
  39. Ablyalimov O. S. On methods for studying the transportation work of locomotives [Text] / O. S. Ablyalimov // Republican scientific and technical conference with the participation of foreign scientists “Resource-saving technologies in railway transport” / Tashkent Institute. Eng. railway transport. – Tashkent, 2011. – pp. 30 – 33. [Google Scholar]
  40. Petrov Yu. P. Variational methods of optimal control theory / Yu. P. Petrov // Monograph. – M.-L.: Energy, 1965, 220 p. [Google Scholar]
  41. Petrov Yu. P. Variational methods of optimal control theory / Yu. P. Petrov // Monograph, 2nd ed. reworked and additional – M.-L.: Energy, 1977, 280 p. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.