Improvement of the method of time rationing for assembling car groups on one track
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- Category: Content №1 2024
- Last Updated on 29 February 2024
- Published on 30 November -0001
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Authors:
D. Kozachenko*, orcid.org/0000-0003-2611-1350, Ukrainian State University of Science and Technologies, Dnipro, Ukrainee-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
B.Gera, orcid.org/0000-0002-5413-5176, Ya.S.Pidstryhach Institute for Applied Problems of Mechanics and Mathematics, National Academy of Sciences of Ukraine, Lviv, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
I.Taran, orcid.org/0000-0002-3679-2519, Dnipro University of Technology, Dnipro, Ukraine; Rzeszow University of Technology, Rzeszow, the Republic of Poland, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
R.Korobiova, orcid.org/0000-0002-6424-1079, Ukrainian State University of Science and Technologies, Dnipro, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
V.Malashkin, orcid.org/0000-0002-5650-1571, Ukrainian State University of Science and Technologies, Dnipro, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Yu.Hermaniuk, orcid.org/0000-0002-4905-8313, Lviv Polytechnic National University, Lviv, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
* Corresponding author e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2024, (1): 147 - 153
https://doi.org/10.33271/nvngu/2024-1/147
Abstract:
Purpose. To improve the method for standardizing the duration of the shunting operation of assembling cars on one track. This can be achieved as a result of solving the following research problems: development of a method for searching the optimal order of assembling cars on one track; distribution parameters estimation of the random value of the duration of shunting operation of assembling cars on one track based on calculation experiments.
Methodology. During the research, the methods of theory of railway operation, dynamic programming and mathematical statistics were used.
Findings. Research on the assembling process of car group to one track established the distribution parameters of the random variable of time spent for shunting. In the course of the research, the problem of choosing the optimal order of shunting operations during car assembling was formalized and solved as a problem of dynamic programming. The time spent for shunting work was chosen as the optimality criterion. The paper considers the possibility of approximating the data of calculation experiments by analytical dependencies. It was found out that the use of linear polynomials with interaction allows obtaining dependencies describing time standards with a relative accuracy of ±5 %.
Originality. The method is improved for developing the time standards for shunting work, which, unlike the existing one, is based on the performance of a series of calculation experiments, each of which solves the optimization problem of finding such an order of assembling cars that ensures minimum time consumption for shunting.
Practical value. The methods developed in the work and the dependencies obtained allow improving the quality of decisions made when developing technology and designing railway stations and sidings of industrial enterprises.
Keywords: railway transport, railway station, siding, shunting work, time standards
References.
1. Fischer, S. (2022). Investigation of the Horizontal Track Geometry regarding Geogrid Reinforcement under Ballast. Acta Polytechnica Hungarica, 19(3), 89-101. https://doi.org/10.12700/APH.19.3.2022.3.8.
2. Szalai, S., Szívós, B. F., Kurhan, D., Németh, A., Sysyn, M., & Fischer, S. (2023). Optimization of Surface Preparation and Painting Processes for Railway and Automotive Steel Sheets. Infrastructures, 8(2), 28. https://doi.org/10.3390/infrastructures8020028.
3. Kou, L., Sysyn, M., Fischer, S., Liu, J., & Nabochenko, O. (2022). Optical Rail Surface Crack Detection Method Based on Semantic Segmentation Replacement for Magnetic Particle Inspection. Sensors, 22(21), 8214. https://doi.org/10.3390/s22218214.
4. Fischer, S. (2022). Geogrid reinforcement of ballasted railway superstructure for stabilization of the railway track geometry – A case study. Geotextiles and Geomembranes, 50(5), 1036-1051. https://doi.org/10.1016/j.geotexmem.2022.05.005.
5. Blackburn, S. R. (2018). Inglenook Shunting Puzzles. ArXiv. https://doi.org/10.48550/arXiv.1810.07970.
6. Falsafain, H., & Tamannaei, M. (2019). A Novel Dynamic Programming Approach to the Train Marshalling Problem. IEEE Transactions on Intelligent Transportation Systems, 1-10. https://doi.org/10.1109/tits.2019.2898476.
7. Dorpinghaus, J., & Schrader, R. (2018). A graph-theoretic approach to the train marshalling problem. Proceedings of the 2018 Federated Conference on Computer Science and Information Systems, 15, 227-231. https://doi.org/10.15439/2018F26.
8. Beygang, K., Krumke, S. O., & Dahms, F. (2010). Train Marshalling Problem-Algorithms and Bounds. Retrieved from https://d-nb.info/1027389848/34.
9. Hansmann, R. S., Zimmermann, U. T., Krebs, H. J., & Jäger, W. (Eds.) (2008). Optimal Sorting of Rolling Stock at Hump Yards. Mathematics – Key Technology for the Future. Berlin, Heidelberg: Springer, 189-203. https://doi.org/10.1007/978-3-540-77203-3_14.
10. Bohlin, M., Gestrelius, S., Dahms, F., Mihalák, M., & Flier, H. (2016). Optimization Methods for Multistage Freight Train Formation. Transportation Science, 50(3), 823-840. https://doi.org/10.1287/trsc.2014.0580.
11. Kozachenko, D., Bobrovskiy, V., Gera, B., Skovron, I., & Gorbova, A. (2021). An optimization method of the multi-group train formation at flat yards. International Journal of Rail Transportation, 9(1), 61-78. https://doi.org/10.1080/23248378.2020.1732235.
12. Jaehn, F., Otto, A., & Seifried, K. (2018). Shunting operations at flat yards: retrieving freight railcars from storage tracks. OR Spectrum, 40, 367-393. https://doi.org/10.1007/s00291-017-0495-x.
13. Hirashima, Y. (2011). A new design method for train marshaling evaluating the transfer distance of locomotive. Intelligent Control and Innovative Computing, 163-176. https://doi.org/10.1007/978-1-4614-1695-1_13.
14. Hirashima, Y. (2016). A reinforcement learning for marshaling of freight train considering collective motions. Proceedings of the International MultiConference of Engineers and Computer Scientists, 1, 19-24. Retrieved from https://www.iaeng.org/publication/IMECS2016/IMECS2016_pp19-24.pdf.
15. Turpak, S. M., Taran, I. O., Fomin, O. V., & Tretiak, O. O. (2018). Logistic technology to deliver raw material for metallurgical production. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu, (1), 162-169. https://doi.org/10.29202/nvngu/2018-1/3.
16. Saukenova, I., Oliskevych, M., Taran, I., Toktamyssova, A., Aliakbarkyzy, D., & Pelo, R. (2022). Optimization of schedules for early garbage collection and disposal in the megapolis. Eastern-European Journal of Enterprise Technologies, 1(3-115), 13-23. https://doi. org/10.15587/1729-4061.2022.251082.
17. Ivic, M., Markovic, M., & Markovic, A. (2007). Effects of the application of conventional methods in the process of forming the pick-up trains. Yugoslav Journal of Operations Research, 17(2), 245-256. https://doi.org/10.2298/YJOR0702245I.
18. Hirashima, Y. (2013). A Reinforcement Learning for Train Marshaling Based on the Processing Time Considering Group Layout of Freight Cars. IAENG Transactions on Electrical Engineering, 1, 229-243. https://doi.org/10.1142/9789814439084_0018.
19. Belosevic, I., & Ivic, M. (2017). Variable Neighborhood Search for Multistage Train Classification at Strategic Planning Level. Computer-Aided Civil and Infrastructure Engineering, 33(3), 220-242. https://doi.org/10.1111/mice.12304.
20. Kozachenko, D., Verlan, A., & Korobyova, R. (2020). Improvement of graphical model of railway stations functioning. 2020 International Conference on Decision Aid Sciences and Application (DASA), 395-398. https://doi.org/10.1109/DASA51403.2020.9317139.
21. Sivitsky, D. A., Karasev, S. V., & Osipov, D. V. (2022). Methodology for Selecting the Multistage Methods of Train Classification and Design Parameters of Specialized Shunting Facilities Based on Modeling. Transportation Research Procedia, 61, 323-332. https://doi.org/10.1016/j.trpro.2022.01.053.
22. Lashenyh, O., Turpak, S., Gritcay, S., Vasileva, L., & Ostroglyad, E. (2016). Development of mathematical models for planning the duration of shunting operations. Eastern-European Journal of Enterprise Technologies, 5/3(83), 40-46. https://doi.org/10.15587/17294061.2016.80752.
23. Kuznetsov, V., Lyubarskyi, B., Kardas-Cinal, E., Yeritsyan, B., Riabov, I., & Rubanik, I. (2020). Recommendations for the selection of parameters for shunting locomotives. Archives of Transport, 56(4), 119-133. https://doi.org/10.5604/01.3001.0014.5650.
24. Kozachenko, D., Dovbnia, M., Ochkasov, O., Serdiuk, V., Shepotenko, A., & Keršys, A. (2018). Rationale for Choosing the Type of Traction Rolling Stock for the Enterprise of Industrial Transport. In Proceedings of 22 nd International Scientific Conference. Transport Means, 2018(2), 991-995. Retrieved from https://transportmeans.ktu.edu/wp-content/uploads/sites/307/2018/02/Transport-means-II-A4-2018-09-25.pdf.
25. Németh, A., & Fischer, S. (2018). Investigation of glued insulated rail joints with special fiber-glass reinforced synthetic fishplates using in continuously welded tracks. Pollack Periodica, 13(2), 77-86. https://doi.org/10.1556/606.2018.13.2.8.
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