Russian Federation
Russian Federation
Russian Federation
Purpose: The train formation plan is a fundamental technological document that affects the rational organization of the operational work of railways of JSCo “Russian Railways”. The amount of operating costs, the stability of the operation of stations, sections and transport hubs depends on its correct development. The existing practice assumes the use of the average values of its design parameters when calculating the train formation plan, without taking into account their variable nature. In this case, it is not always possible to guarantee that the optimal decision is taken on the organization of car traffic. The purpose of the article is to describe a method for taking into account the variable nature of the design parameters of the train formation plan, which will increase the stability of its individual assignments to the unevenness of operational work. Methods: Methods of theoretical analysis are used, existing analytical dependencies are described, which allow determining the calculated parameters of the train formation plan. Fuzzy set theory and its natural extension, fuzzy mathematics, have been used to describe the variable nature of the calculated parameters. To make an optimal decision on the adjustment of individual assignments of the train formation plan, the methods of decision-making theory have been used, namely, the Bellman-Zadeh method of decision-making in fuzzy conditions. Results: Calculation formulas have been obtained that allow determining the design parameters of the train formation plan in conditions of uneven operational work directly, without using auxiliary tables and graphs, having information only about the fluctuations of the car traffic of a specific purpose of the formation plan. A method has been developed for determining the threshold value of the car traffic, optimal in conditions of unevenness. Practical significance: Taking into account the variable nature of the design standards of the train formation plan during its development will increase the stability of its specific assignments, reduce operating costs for its implementation during the life cycle, reduce the number of operational adjustments.
Threshold value of car traffic, fuzzy sets, unevenness of car traffic, linguistic model for extracting the train flow
1. Xiao J. Comprehensive optimization of the one-block and two-block train formation plan / J. Xiao, B. Lin // Journal of Rail Transport Planning & Management. - 2016. - URL: http://dx.doi.org/10.1016/j.jrtpm.2016.09.002.
2. Yaghini M. Solving railroad blocking problem using ant colony optimization algorithm / M. Yaghini, A. Foroughi, B. Nadjari // Applied Mathematical Modelling. - 2011. - Iss. 35. - Pp. 5579-5591. - DOI:https://doi.org/10.1016/j.apm.2011.05.018.
3. Yaghini M. A fuzzy railroad blocking model with genetic algorithm solution approach for Iranian railways / M. Yaghini, M. Momeni, M. Sarmadi et al. // Applied Mathematical Modelling. - 2015. - Iss. 39. - Pp. 6114-6125. - DOI:https://doi.org/10.1016/j.apm.2015.01.052.
4. Kukushkina Ya. V. Zavisimost' velichiny perehodyaschego ostatka ot nakopleniya smezhnyh sostavov / Ya. V. Kukushkina // Izvestiya Peterburgskogo universiteta putey soobscheniya. - 2010. - № 3(24). - S. 132-140.
5. Pankov A. N. O sostavoobrazovanii na sortirovochnyh stanciyah / A. N. Pankov, V. A. Kudryavcev, Ya. V. Kukushkina i dr. // Zheleznodorozhnyy transport. - 2016. - № 3. - S. 45-50.
6. Zadeh L. A. Fuzzy Sets / L. A. Zadeh // Information and Control. - 1965. - Vol. 8. - Pp. 338-353.
7. Dolgopolov P. Optimization of train routes based on neuro-fuzzy modeling and genetic algorithms / P. Dolgopolov, D. Konstantinov, L. Rybalchenko et al. // Procedia Computer Science. - 2019. - Iss. 149. - Pp. 11-18. - DOI:https://doi.org/10.1016/j.procs.2019.01.101.
8. Milenković M. A fuzzy random model for rail freight car fleet sizing problem / M. Milenković, N. Bojović // Transportation Research Part C: Emerging Technologies. - August 2013. - Vol. 33. - DOI:https://doi.org/10.1016/j.trc.2013.05.003.
9. Yang L. Railway freight transportation planning with mixed uncertainty of randomness and fuzziness / L. Yang, Z. Gao, K. Li // Applied Soft Computing. - January 2011. - Vol. 11. - Iss.1. - DOI:https://doi.org/10.1016/j.asoc.2009.12.039.
10. Schneider M. Minimising economic losses due to inefficient rescheduling / M. Schneider, N. Nießen // Journal of Rail Transport Planning & Management. - 2016. - DOI:https://doi.org/10.1016/j.jrtpm.2016.05.002.
11. Yang Z. Semi-active Control of High-speed Trains Based on Fuzzy PID Control / Z. Yang, J. Zhang, Z. Chen et al. // Procedia Engineering. - 2011. - Iss. 15. - Pp. 521-525. DOI:https://doi.org/10.1016/j.proeng.2011.08.099.
12. Badeckiy A. P. Ispol'zovanie samonastraivayuschihsya nechetkih modeley dlya prinyatiya resheniy o korrektirovke naznacheniy plana formirovaniya poezdov / A. P. Badeckiy, O. A. Medved' // Transport Rossii: problemy i perspektivy - 2016: materialy mezhdunarodnoy nauchno-prakticheskoy konferencii. - SPb.: IPTRAN, 2016. - S. 221-224.
13. Os'minin A. T. Modul' operativnoy korrektirovki naznacheniy plana formirovaniya poezdov / A. T. Os'minin, I. I. Os'minina, A. P. Badeckiy i dr. // Intellektual'nye sistemy upravleniya na zheleznodorozhnom transporte. Komp'yuternoe i matematicheskoe modelirovanie (ISUZhT-2016): trudy pyatoy nauchno-tehnicheskoy konferencii. - M.: NIIAS, 2016. - S. 86-89.
14. Alekseychik T. The choice of transport for freight and passenger traffic in the region, using econometric and fuzzy modeling / T. Alekseychik, T. Bogachev, V. Bogachev et al. // Procedia Computer Science. - 2017. - Iss. 120. - Pp. 830-834. - DOI:https://doi.org/10.1016/j.procs.2017.11.314.
15. Kovalev K. E. Mehanizm diagnostiki ekspluatacii malointensivnyh zheleznodorozhnyh liniy na osnove nechetkogo modelirovaniya / K. E. Kovalev, A. V. Novichihin, I. L. Sakovich i dr. // Avtomatika na transporte. - 2023. - T. 9. - № 1. - S. 72-86
16. Rybin P. K. Metod optimizacii struktury neyronnoy seti dlya zadachi planirovaniya podvoda poezdov k priportovym stanciyam / P. K. Rybin, R. V. Gorin // Vestnik transporta Povolzh'ya. - 2017. - № 5. - S. 55-63
17. Yugrina O. Specific features of the railway polygon operation with empty car traffic / O. Yugrina, L. Zharikova, A. Bessolitsyn et al. // International Scientific Siberian Transport Forum TransSiberia - 2021. Vol. 2. Lecture Notes in Networks and Systems. - 2022. - Pp. 376-384. - DOI:https://doi.org/10.1007/978-3-030-96383-5_42.
18. Os'minin A. T. Uvelichenie propusknyh i provoznyh sposobnostey za schet povysheniya effektivnosti perevozochnogo processa i transportnogo obsluzhivaniya / A. T. Os'minin // Byulleten' ob'edinennogo uchenogo soveta OAO «RZhD». - 2018. - № 2. - S. 14-31
19. Os'minin A. T. Reinzhiniring modeli upravleniya perevozochnym processom / A. T. Os'minin // RZhD-Partner. - 2020. - № 1-2. - S. 46-49.
20. Os'minin A. T. Sovershenstvovanie sistemy planirovaniya perevozok gruzov / A. T. Os'minin, I. G. Belozerova // Zheleznodorozhnyy transport. - 2020. - № 3. - S. 17-21.
21. Os'minin A. T. Organizaciya gruzovyh perevozok i upravlenie tovaropotokami v cepochke sozdaniya stoimosti / A. T. Os'minin // Tehnik transporta: obrazovanie i praktika. - 2020. - T. 1. - № 2. - S. 94-105.
22. Kudryavcev V. A. Uchet kolebaniy vagonopotokov pri raschete plana formirovaniya poezdov / V. A. Kudryavcev, A. P. Badeckiy // Izvestiya Peterburgskogo universiteta putey soobscheniya. - 2012. - № 3. - S. 10-16.
23. Badetskii A. P. Improving the Stability of the Train Formation Plan to Uneven Operational Work / A. P. Badetskii, O. A. Medved // Transportation Research Procedia, Novosibirsk, 25-29 maya 2020 goda. - Novosibirsk, 2021. - Pp. 559-567. - DOI:https://doi.org/10.1016/j.trpro.2021.02.108.
24. Badeckiy A. P. Razrabotka raschetnyh vagonopotokov plana formirovaniya poezdov s uchetom ih neravnomernosti / A. P. Badeckiy // Vestnik transporta Povolzh'ya. - 2013. - № 3. - S. 53-60.
25. Instruktivnye ukazaniya po organizacii vagonopotokov na zheleznyh dorogah OAO «RZhD». - M., 2007. - 547 s.
26. Badeckiy A. P. Uchet peremennogo haraktera raschetnyh normativov plana formirovaniya poezdov s ispol'zovaniem tehnologiy vychislitel'no intellekta / A. P. Badeckiy, O. A. Medved', Ya. V. Kukushkina // Byulleten' rezul'tatov nauchnyh issledovaniy. - 2023. - Vyp. 3. - S. 32-45. - DOI:https://doi.org/10.20295/2223-9987-2023-3-32-45
27. Badeckiy A. P. Vliyanie kolebaniy vagonopotoka na parametr nakopleniya / A. P. Badeckiy // Transport Rossii: problemy i perspektivy - 2014: materialy mezhdunarodnoy nauchno-prakticheskoy konferencii. - SPb., 2014. - S. 191-195.
28. Kotenko A. G. Opredelenie porogovogo znacheniya vagonopotoka, optimal'nogo v usloviyah neravnomernosti / A. G. Kotenko, A. P. Badeckiy, A. S. Bessolicyn // Vestnik transporta Povolzh'ya. - 2013. - № 4. - S. 20-27.
29. Bellman R. Zade L. Prinyatie resheniy v rasplyvchatyh usloviyah / R. Bellman, L. Zade // Voprosy analiza i procedury prinyatiya resheniy. - M.: Mir, 1976. - C. 172-215.
