Interdependence of car traffic volumes operation modes

Introduction. The tasks of car traffic volumes operation in terms of possible changes of service conditions have three solution modes (normative train make-up plan, its periodic changes and operative orders), each of which has its own structure of objective functions, tuning characteristics of controlled variables and constraints, which is the subject of the article. The objective of the article is a formalised statement of the problem and the principal methods of its solution in these modes.

Materials and methods. The methods and provisions of the theory of car traffic volumes organisation, the theory of interaction of station processes, set theory, graph theory, and nonlinear mathematical programming are used. The initial data for solving the problems of the car traffic volumes organisation are presented in the form of a structured set of interdependent network models of average daily car traffic volumes and dynamic data on the location of cars. The controlled variables are the sets of goods train destinations and routes, as well as signs of attachment of car traffic volumes to train destinations and train destinations to routes. The objective function is subject to infrastructural, logistical and resource constraints that are interdependent. The objective function of the train make-up plan calculating provides for minimising the average daily cost of promoting car traffic. In the paradigm of the lifecycle of the car traffic volumes operation it is supplemented by a component that considers the cost of transitions between the periods of operation and operating modes of the car traffic volumes organisation system.

Results. The need for adjustments to the make-up plan is caused by a change in the flow structure or the availability of resources and is assessed based on a comparison of the working car fleet balance and normative on the railway network division. Depending on this ratio, the authors fundamentally define a set of strategies for finding solutions to normalisation the car traffic volumes organisation system.

Discussion and conclusion. The provisions presented in the article are the basis for further structural adjustment of the used economic and mathematical tools for calculating the train make-up plan by the method of step-by-step distribution of car traffic across a network of acceptable train assignments to effectively solve the defined tasks.

1. Borodin A. F., Nikolaev K. Yu., Prozorov V. V., Shinderov R. V. Logistical, infrastructural and resource constraints in car traffic streams operation. Polytransport Systems: Proceedings of the Eighth All-Russian Scientif ic and Technical Conference, 24–25 th October, 2024. Novosibirsk: SGUPS; 2024. P. 80–84. (In Russ.). EDN: https://elibrary.ru/lzkmro.

2. Baturin A. P., Borodin A. F., Panin V. V., Shumskaya O. A., Poyarkova M. A. Organisation of network car traf f ic streams into one-group trains. Railway Transport. 2005;(6):17–24. (In Russ.).

3. Borodin A. F., Verbov D. M., Rubtsov D. V., Novikov P. O. Automated system for car traffic streams organisation: modern theory and practice.Railway Transport. 2021;(11):4–17. (In Russ.). EDN: https://elibrary.ru/ndafsl.

4. Novikov P. O., Shinderov R. V., Shchepanov A. L., Sukhov A. A., Dmitriev E. O. Solving tasks for automated calculation of normative technology for car traffic streams organisation, operative management, and logical control. MLSD’2021: Proceedings of Fourteenth International Conference, 27–29 th September, 2021. Moscow: V. A. Trapeznikov Institute of Control Sciences of RAS; 2021. P. 1020–1027. (In Russ.). EDN: https://elibrary.ru/lipnhi.

5. Kutyrkin A. V. Comprehensive model for car traffic streams planning and operation. Improvement of Operational Work of Railways. Proceedings of VNIIZHT. Moscow: Transport; 1985. P. 68–77. (In Russ.).

6. Kutyrkin A. V. Algorithms for operative adjustment of train make-up plan. Vestnik VNIIZHT. 1983;(8):1–6. (In Russ.).

7. Kutyrkin A. V., Pavlovsky A. A. Optimal management of car traffic streams under uncertain initial data. Science and Technology in Transport. 2003;(3):40–53. (In Russ.). EDN: https://elibrary.ru/hvyuwz.

8. Os’minin A. T. Intelligent management system for transportation processes in railway transport. Bulletin of the Unified Scientific Council of JSC “RZD”. 2021;(1):1–17. (In Russ.).

9. Os’minin A. T., Shapkin I. N. Optimisation of the system for car traffic streams organisation based on digital technologies in railway transport and client-oriented principles. F. P. Kochnev: Proceedings of International Scientific and Practical Conference, 22–23 rd April, 2021. Moscow: RUT (MIIT); 2021. P. 231–239. (In Russ.). EDN: https://elibrary.ru/bpabwp.

10. Os’minin A. T., Badetsky A. P. Multi-agent system for the adaptive train make-up plan calculating. ISUZhT-2015: Proceedings of Fourth Scientific and Technical Conference, 18 th November, 2015. Moscow: NIIAS; 2015. P. 61–65. (In Russ.). EDN: https://elibrary.ru/bfbknk.

11. Negrey V. Ya., Shkurin K. M. Synergetic approach to the onegroup train make-up plan calculating. Science and Progress in Transport. 2018;(5(77)):53–64. (In Russ.). https://doi.org/10.15802/stp2018/147718. EDN: https://elibrary.ru/ytfxbb.

12. Litvinova I. M., Kozlov V. G. Information-analytical model for distributing sorting work at the stations of the Belarusian Railway. Tikhomirov Readings: Proceedings of International Scientific and Practical Conference, 30 th November, 2018. Gomel: BSUT; 2019. P. 99–102. (In Russ.). EDN: https://elibrary.ru/tequmn.

13. Yerofeev A. A., Kozlov V. G., Tereshchenko O. A., Litvinova I. M., Sladkevich A. N. Accelerating the movement of car traffic streams: experience of the Belarusian Railway. Railway Transport. 2025;(8):34–39. (In Russ.). EDN: https://elibrary.ru/ukdafa.

14. Kozlov V. G. Increasing the efficiency of technical routing based on the dynamic model for the parameters of car traffic streams correspondences calculating and evaluating. UERT-2022: Proceedings of International Scientific and Practical Conference, 15–16 th March, 2022. St. Petersburg: PGUPS; 2022. P. 364–368. (In Russ.). EDN: https://elibrary.ru/mlzniu.

15. Kekish N. A. Improving the efficiency of the low-power car traffic streams organisation using the system of interrelated group trains. Collected scientific works of UkrSURT. 2017;(167):42–54. (In Russ.).

16. Xiao J., Lin B. Comprehensive optimisation of the one-block and two-block train formation plan. Journal of Rail Transportation Planning & Management. 2016;6(3):218–236. https://doi.org/10.1016/j.jrtpm.2016.09.002.

17. Poliński J., Ochociński K. Cyfryzacja w transporcie kolejowym. Problemy Kolejnictwa. 2020. Zeszyt 188. S. 53–65. https://doi.org/10.36137/1885P.

18. Borodin A. F., Sotnikov E. A. Rational ratio of track capacities of stations and car fleets considering the increase in the share of private cars. Railway Transport. 2011;(3):8–19. (In Russ.). EDN: https://elibrary.ru/nxlpnj.