MATHEMATICAL MODEL OF THE RAILWAY OPERATION OPTIMIZATION TO INCREASE A RAILWAY SECTION CAPACITY
Abstract and keywords
Abstract (English):
Formalization of a railway section operation for simulation and digital operation models to improve a railway section capacity. Methods: The methodological basis of the research is a system approach in which the research object is considered as a complex system consisting of interacting subsystems and elements. Dynamic and neural network programming methods as well as tools for structural analysis, algorithmization and modeling of complex control systems are used. Results: The study presents the main entities related to the management of the railway section operation, their conditions, algorithms of mutual influence, as well as parameters for evaluating the management effectiveness. The formalization of the identification parameter hierarchy of a railway section and its infrastructure to create a digital double and neural network control procedures has been carried out. An approach to the development of operational and technological solutions aimed at the effective use of railway section capacities and network routes using digital doubles and artificial intelligence technologies is proposed. Practical significance: Indicators of different levels of railway section management, transport infrastructure and train operation on the section affecting the rail capacity are presented. Formalization of railway transport objects and processes will be important for further research in the field of artificial intelligence technologies as well as for the development and implementation of intelligent technologies in transportation management. Approbation of the proposed model has been carried out based on the ‘Virtual railway’ training laboratory complex in order to improve practical skills in applying artificial intelligence in the transportation management.

Keywords:
Railway section, throughput, mathematical model, digital model, neural network control
Text
Text (PDF): Read Download
References

1. Metodika opredeleniya propusknoy i provoznoy sposobnostey infrastruktury zheleznodorozhnogo transporta obschego pol'zovaniya. — Utverzhdena prikazom Mintransa Rossii ot 18 iyulya 2018 goda № 266.

2. Mamaev E. A. Logistika i transport v cifrovoy ekonomike / E. A. Mamaev // Sb. nauch. tr. II mezhdunar. nauch.-prakt. konf. «Transport i logistika: innovacionnaya infrastruktura, intellektual'nye i resursosberegayuschie tehnologii, ekonomika i upravlenie». — Rostov-na-Donu: Rost. gos. un-t. putey soobscheniya, 2018. — S. 8–12.

3. Baginova V. V. Cifrovye tehnologii transportnogo holdinga / V. V. Baginova, B. A. Levin, E. A. Mamaev // Logistika i upravlenie cepyami postavok. — 2021. — № 6(105). — S. 16–19.

4. Mamaev E. A. Modeli soglasovannogo razvitiya elementov logisticheskih cepey / E. A. Mamaev // Sb.: nauch. Trudov «Sovremennoe razvitie nauki i tehniki» («Nauka-2017»). — T. 2. Tehnicheskie, ekonomicheskie i yuridicheskie nauki. — Rostov-na-Donu: Rost. gos. un-t. putey soobscheniya, 2017. — S. 160–162.

5. Mamaev E. A. Cifrovaya logistika v smeshannyh perevozkah v mezhdunarodnom soobschenii / E. A. Mamaev // Sb. nauch. tr. III mezhdunar. nauch.-prakt. konf. «Transport i logistika: strategicheskie prioritety, tehnologicheskie platformy i resheniya v globalizovannoy cifrovoy ekonomike». — Rostov-na-Donu: Rost. gos. un-t. putey soobscheniya. — 2019. — S. 243–248.

6. Belyh A. A. Ocenka vliyaniya iskusstvennogo intellekta na operativnoe upravlenie uchastkovoy zhelezno-dorozhnoy stancii / A. A. Belyh, V. V. Shirokova // Nacional'naya Associaciya Uchenyh. — 2020. — № 56-1(56). — S. 36–41. — DOI:https://doi.org/10.31618/nas.2413- 5291.2020.1.56.229.

7. Mamaev E. A. Cifrovizaciya transportnogo biznesa i razvitie logisticheskogo servisa dlya transportnogo holdinga s primeneniem tehnologii BIGDATA / E. A. Mamaev, M. V. Kolesnikov // XIV Vserossiyskaya mul'tikonferenciya po problemam upravleniya (MKPU- 2021): materialy XIV mul'tikonferencii (Divnomorskoe, Gelendzhik, 27 sentyabrya — 2 oktyabrya 2021 g.): v 4 t. Yuzhnyy federal'nyy universitet [redkol.: I. A. Kalyaev, V. G. Peshehonov i dr.]. — Rostov-na-Donu; Taganrog: Izd-vo Yuzhnogo federal'nogo universiteta. — 2021. — T. 4. — S. 134–136.

8. Kuznecov V. G. Formirovanie integrirovannoy tehnologii organizacii vagonopotokov i dvizheniya gruzovyh poezdov v cifrovoy modeli zheleznoy dorogi / V. G. Kuznecov, E. A. Fedorov, V. G. Kozlov // Intellektual'nye transportnye sistemy: mat-ly Mezhdunar. nauchno-prakt. konf. — M., 2022. — S. 204–214.

9. Rahmangulov A. N. Imitacionnye modeli v cifrovyh dvoynikah zheleznodorozhnyh stanciy / A. N. Rahangulov, P. N. Mishkurov, D. V. Aleksandrin // Akademik Vladimir Nikolaevich Obrazcov — osnovopolozhnik transportnoy nauki: trudy mezhdunar. nauchno-prakt. konf., posvyaschennoy 125-letiyu universiteta. — M., 2021. — S. 574–582. — DOI:https://doi.org/10.47581/2022/Obrazcov.76.

10. Moskvicheva E. E. K voprosu prakticheskoy realizacii cifrovizacii gruzovyh stanciy / E. E. Moskvicheva // Nauka i obrazovanie transportu. — 2022. — № 1. — S. 159–161.

11. Shabel'nikov A. N. Perspektivy sovershenstvovaniya KSAU SP v ramkah koncepcii cifrovoy zheleznodorozhnoy stancii / A. N. Shabel'nikov, N. N. Lyabah // Intellektual'nye sistemy upravleniya na zheleznodorozhnom transporte. Komp'yuternoe i matematicheskoe modelirovanie (ISUZhT-2018). Trudy sed'moy nauchno- tehnicheskoy konf. — 2018. — S. 117–119.

12. Shilin A. O. Vnedrenie KSAU SP v ramkah koncepcii cifrovoy zheleznodorozhnoy stancii / A. O. Shilin // Voprosy nauki. — 2022. — № 3. — S. 73–77.

13. Kozlov P. A. O tehnologii rascheta zheleznodorozhnyh stanciy / P. A. Kozlov, V. S. Kolokol'nikov, A. O. Shmidt // Tendencii razvitiya zheleznodorozhnogo transporta i upravleniya perevozochnym processom: matly Mezhdunar. yubileynoy nauchno-tehnicheskoy konf.,posvyaschennoy 95-letiyu kafedr «Zheleznodorozhnye stancii i transportnye uzly», «Upravlenie ekspluatacionnoy rabotoy i bezopasnost'yu na transporte». — M., 2020. — S. 41–47.

14. Chebotareva E. A. Modelirovanie elementov professional'noy intuicii v cheloveko-mashinnyh sistemah dlya resheniya zadach operativnogo upravleniya zheleznodorozhnym transportom / E. A. Chebotareva // Mir transporta i tehnologicheskih mashin. — 2023. — № 3-4(82). — S. 61–69. — DOI:https://doi.org/10.33979/2073-7432-2023- 3-4(82)-61-69.

15. Shevchenko D. V. Metodologiya postroeniya cifrovyh dvoynikov na zheleznodorozhnom transporte / D. V. Shevchenko // Vestnik Nauchno-issledovatel'skogo instituta zheleznodorozhnogo transporta. — 2021. — T. 80. — № 2. — S. 91–99. — DOI:https://doi.org/10.21780/2223-9731- 2021-80-2-91-99.

16. Lychkina N. N. Koncepciya cifrovogo dvoynika i rol' imitacionnyh modeley v arhitekture cifrovogo dvoynika / N. N. Lychkina, V. V. Pavlov // Imitacionnoe modelirovanie. Teoriya i praktika (IMMOD-2023): sbornik trudov odinnadcatoy vserossiyskoy nauchno-prakt. konf. po imitacionnomu modelirovaniyu i ego primeneniyu v nauke i promyshlennosti. — Kazan', 2023. — S. 139–149.

17. Kurtikova E. R. Primenenie neyronnyh setey dlya klassifikacii zheleznodorozhnyh stanciy / E. R. Kurtikova, D. A. Shevchenko, V. A. Karzakov // V sbornike: Kochnevskie chteniya — 2023: sovremennaya teoriya i praktika ekspluatacionnoy raboty zheleznyh dorog. Trudy II-y Mezhdunar. nauchno-prakt. konf. M., 2023. — S. 359–362.

18. Mishkurov P. N. Osobennosti postroeniya agentnoy imitacionnoy modeli zheleznodorozhnoy stancii / P. N. Mishkurov, A. N. Rahmangulov // Sovremennye problemy transportnogo kompleksa Rossii. — 2021. — T. 11. — № 1. — S. 29–40. — DOI:https://doi.org/10.18503/2222-9396- 2021-11-1-29-40.

19. Erofeev A. A. Tehnologii iskusstvennogo intellekta pri reshenii ekspluatacionnyh zadach v sisteme smenno-uchetnogo planirovaniya gruzovoy raboty zheleznodorozhnyh stanciy / A. A. Erofeev // Problemy perspektivnogo razvitiya zheleznodorozhnyh stanciy i uzlov. — 2022. — № 1(4). — S. 102–108.

20. Chebotareva E. A. Analiz meropriyatiy po povysheniyu propusknoy sposobnosti uchastkov Severo- Kavkazskoy zheleznoy dorogi / E. A. Chebotareva. // Transport: nauka, tehnika, upravlenie. — 2022. — № 1. — S. 29–34. — DOI:https://doi.org/10.36535/0236-1914-2022-01-5.

Login or Create
* Forgot password?