Russian Federation
Russian Federation
Purpose: Adaptation of methods of constructing models of transport networks for the development of rational multimodal routes of regional passenger transportation, as well as the creation of a software product for the practical implementation of the proposed algorithms. Methods: Mathematical modeling; graph theory for solving regional transportation problems with construction of two-level oriented weighted multigraphs; Analysis of existing algorithms for optimizing the search for graph solutions; Dijkstra’s algorithm. Results: The model of the regional passenger transport network has been implemented in the form of a calculation program developed by the authors. In this program, the schedule of the movement of all transport points under consideration is the initial data, and the result is the construction of rational multimodal routes. The calculation program is compiled from several modules that implement the following functionality in general: reading input data from files; the formation of an array of connections for the problems under consideration; search for a rational solution and output of the received data while saving it to the file. The optimization criterion when choosing a route can be the minimum travel time, distance, or cost of the trip, depending on the task and input data provided. The resulting array of data with the results has been further analyzed using the MS Excel table editor. This approach is selected due to sufficient flexibility when performing a variety of data analysis and the convenience of graphic presentation of the results. Practical significance: The development of rational multimodal routes, relevant primarily for cases of abrupt changes in transport relations, in which the extrapolation methods of existing passenger flow do not provide reliable forecast data. Justification of the adjustment of the schedules of regional passenger routes based on the results of the analysis of the demand and the load of their specific segments.
Multimodal route, passenger transportation, regional transport network, regional transport, graph theory, mathematical model
1. Dorofeevskiy S. A. Effektivnye parametry kompleksnoy tehnologii transportnogo uzla / S. A. Dorofeevskiy, A. N. Ivankov, V. V. Kostenko // Zheleznodorozhnyy transport. - 2015. - № 4. - S. 49-53.
2. Binder S. The multi-objective railway timetable rescheduling problem / S. Binder, Y. Maknoon, M. Bierlaire // Transportation Research Part C: Emerging Technologies. - Vol. 78. - Pp. 78-94. - DOI:https://doi.org/10.1016/j.trc.2017.02.001.
3. Kostenko V. V. Optimization of regional transport networks based on a mathematical model of passenger preferences / V. V. Kostenko, V. A. Golubtsov, R. V. Pank et al. // Journal of Physics Conference Series. - DOI:https://doi.org/10.1088/1742-6596/2131/3/032101
4. Zhuravleva N. Mathematical description and modelling of transportation of cargoes on the base digital railway / N. Zhuravleva, I. Guliy, M. Polyanichko // Vide. Tehnologija. Resursi - Environment, Technology, Resources, Rezekne, June 20-22, 2019. - Rezekne: Rēzeknes Tehnoloģiju akadēmija, 2019. - Pp. 175-179. - DOI:https://doi.org/10.17770/etr2019vol2.4049.
5. Harary F. Graph Theory. - Reprint 2013. Narosa Publishing House. - P. 298.
6. Egorov Y. The level of railway rates as a factor of sustainable development of territories (Conference Paper) / Y. Egorov, N. Zhuravleva, M. Poliak // 1st Conference on Sustainable Development: Industrial Future of Territories, IFT 2020; Ural State University of Economics Yekaterinburg; Russian Federation; 28 September 2020 to 29 September 2020. - 2020. - Vol. 208.
7. Kotenko A. Analysis of the experience of operation and scope of application of direct connections to ensure passenger transportation on regional lines / A. Kotenko, T. Malakhova, T. Shchmanev // Lecture Notes in Civil Engineering. - 2020. - Vol. 49. - Pp. 363-372. - DOI:https://doi.org/10.1007/978-981-15-0450-1_37.
8. Bollobás B. Modern Graph Theory / B. Bollobás. - 2nd printing 2002. Graduate Texts in Mathematics. 184. Springer Publ. - 394 p. - DOI:https://doi.org/10.1007/978-1-4612-0619-4.
9. Cormen T. H. Introduction to Algorithms / T. H. Cormen, Ch. E. Leiserson, L. Rivest et al. - MIT Press, 2009.
10. Stuart J. Russel and Peter Norvig. Artificial Intelligence: A Modern Approach // J. Stuart. - Prentice Hall Publ., 2020.
11. Dijkstra E. W. A note on two problems in connexion with graphs. - Springer Publ., 1959. - Vol. 1. - Iss. 1. - Pp. 269-271. - DOI:https://doi.org/10.1007/BF01386390
12. Fredman M. L. Fibonacci heaps and their uses in improved network optimization algorithms / M. L. Fredman, R. E. Tarjan // J. ACM. - 1987. - Vol. 34. - Iss. 3. - Pp. 596-615.
13. Svidetel'stvo o gosudarstvennoy registracii programmy dlya EVM № 2023664574 Rossiyskaya Federaciya. Marshrut - programma postroeniya transportnogo marshruta po zadannomu kriteriyu optimizacii: № 2023663295: zayavl. 19.06.2023: opubl. 05.07.2023 / V. A. Golubcov, V. V. Kostenko; zayavitel' aederal'noe gosudarstvennoe byudzhetnoe obrazovatel'noe uchrezhdenie vysshego obrazovaniya «Peterburgskiy gosudarstvennyy universitet putey soobscheniya Imperatora Aleksandra I».
