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Basic Framework for Adjusting the Freight Train Schedule

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Computational Science and Its Applications – ICCSA 2019 (ICCSA 2019)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11620))

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Abstract

Robustness of the train schedule is ensured by use of time margins. The features of each particular section and disturbing factors are not sufficiently taken into account when a master train schedule is created. The paper studies the methodology of effective scheduling the freight train traffic according to the criteria of economic efficiency and punctuality. The methods are proposed for group and individual traffic adjustments. Statistical characteristics of freight train traffic on the main railway line are investigated. The framework of finding margins to the departure headways based on statistical analysis is described. This improvement aimed increasing the punctuality and economic efficiency of freight traffic. The theoretical conclusions are confirmed by statistical data obtained on the Russian railways.

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References

  1. Chebotarev, V., Davydov, B., Godyaev, A.: Stochastic traffic models for the adaptive train dispatching. In: Proceedings of the First International Scientific Conference “Intelligent Information Technologies for Industry” (IITI 2016). Advances in Intelligent Systems and Computing, vol. 451, pp. 323–333 (2016). https://doi.org/10.1007/978-3-319-33816-3_32

  2. Karetnikov, A.D.: In: Karetnikov, A.D., Vorob’ev, N.A. (eds.) Grafik dvizheniya poezdov, Transport, 301 (1979)

    Google Scholar 

  3. Schaafsma, A.: Dynamisch Railverkeersmanagement, besturings-concept voor railverkeer op basis van het Lagenmodel Verkeer en Vervoer: PhD thesis-Delft, The Netherlands, p. 165 (2001)

    Google Scholar 

  4. D’Ariano, A., Pranzo, M., Hansen, I.: Conflict resolution and train speed coordination for solving real-time timetable perturbations. IEEE Trans. Intell. Transp. Syst. 8(2), 208–222 (2007)

    Article  Google Scholar 

  5. Quan, L., Dessouky, M., Leachman, R.C.: Modeling train movements through complex rail networks. ACM Trans. Model. Comput. Simul. 14, 32–76 (2004)

    Google Scholar 

  6. Baranov, L.A., Erofeev, E.V., Melyoshin, I.S., CHin’, L.M.: Optimizaciya upravleniya dvizheniem poezdov: pod red. MIIT, 164 s. (2011)

    Google Scholar 

  7. Klimanov, V.S.: Voprosy operativnogo regulirovaniya poezdopotokov na napravlenii: diss… kand. tekh. nauk: 05 12 08. Klimanov Vladimir Sergeevich. 213 s (1982)

    Google Scholar 

  8. Nikiforov, B.D., Tishkin, E.M., Makarov, V.M., V.S.Klimanov: Upravlenie poezdnoj rabotoj na napravlenii: ZHeleznodorozhnyj transport, vol. 2, S.17–24 (1982)

    Google Scholar 

  9. Levin, D.Y.: Teoriya operativnogo upravleniya perevozochnym processom: monografiya: GOU «Uchebno-metodicheskij centr po obrazovaniyu na zheleznodorozhnom tr-te», 625 s (2008)

    Google Scholar 

  10. SHapkin, I.N., YUsipov, R.A., Kozhanov, E.M.: Modelirovanie poezdnoj raboty na osnove mnogo-faktornogo normirovaniya tekhnologicheskih operacij: Vestnik VNIIZHT, vol. 4, S.30–36 (2004)

    Google Scholar 

  11. Mohon’ko, V.P., Isakov, V.S., Kurenkov, P.V.: Situacionnoe upravlenie perevozochnym processom: Transport: nauka, tekhnika, upravlenie, vol. 11, S. 14–16 (2004)

    Google Scholar 

  12. Ivnickij, V.A., Poplavskij, A.A.: Problema perekhoda k informacionno-upravlyayushchemu rezhimu v sisteme operativnoj organizacii perevozochnogo processa: Vestnik VNIIZHT, vol. 1, S.15–21 (2007)

    Google Scholar 

  13. Cordeau, J.-F., Toth, P., Vigo, D.: A survey of optimization models for train routing and scheduling. Transp. Sci. 32(4), 380–404 (1998)

    Article  Google Scholar 

  14. Jamili, A., et al.: Solving a periodic single-track train timetabling problem by an efficient hybrid algorithm. Eng. Appl. Artif. Intell. 25, 793–800 (2014)

    Article  Google Scholar 

  15. Abramov, A.A., Skobelev, P.O., Belousov, A.A., Eremin, A.S., Belov, M.V.: Mul’tiagentnye tekhnologii adaptivnogo postroeniya grafika dvizheniya poezdov: Intellektual’nye sistemy upravleniya na zheleznodorozhnom transporte, Trudy vtoroj nauchno-tekhnicheskoj konferencii, ISUZHT-2013, Moskva, S.27–29 (2013)

    Google Scholar 

  16. Umanskij, V.I.: Ob organizacii propuska poezdov v period tekhno-logicheskih «okon»: ZHeleznodorozhnyj transport, vol. 9, S.21–24 (2009)

    Google Scholar 

  17. Abril, M., Barber, F., Ingolotti, L., Salido, M.A., Tormos, P., Lova, A.: An assessment of railway capacity. Transp. Res., Part E: Logistics and Transp. Rev. 44(5), 774–806 (2008)

    Article  Google Scholar 

  18. Cacchiani, V., Huisman, D., Kidd, M., Kroon, L., Toth, P., Veelenturf, L., Wagenaar, J.: Overview of recovery models and algorithms for real-time railway rescheduling. Transp. Res. Part B 63, 15–37 (2014)

    Article  Google Scholar 

  19. Törnquist, J.: Computer-based decision support for railway traffic scheduling and dispatching: a review of models and algorithms. In: 5th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2005), Palma de Mallorca, Spain, pp. 114–127 (2015)

    Google Scholar 

  20. Sotnikov, E.A., SHapkin, I.N.: EHkspluatacionnaya rabota na zheleznyh dorogah mira: ZHeleznodorozhnyj transport, vol. 2, S.72–77 (2009)

    Google Scholar 

  21. Kecman, P., Goverde, M., Van den Boom, A.: A model-pre-dictive control framework for railway traffic management. In: Proceedings of the 3th International Seminar on Railway Operations Modelling and Analysis, pp. 57–72 (2011)

    Google Scholar 

  22. Lazarev, A.A., Musatova, E.G., Gafarov, E.R., Kvarackheliya, A.G.: Teoriya raspisanij. Zadachi zheleznodorozhnogo planirovaniya: FGBU nauki Institut problem upravleniya im. V. A. Trapeznikova RAN, 287 s (2012)

    Google Scholar 

  23. Huisman, D., Kroon, L., Lentink, R., Vromans, M.: Operations research in passenger railway transportation: research paper. Erasmus Research Institute of Management (ERIM), ERS-2005-023-LIS. p. 46 (2005)

    Google Scholar 

  24. Muhlhans, E.: Berechnung der Verspatungsentwicklung bei Zug- fahrten: Eisenbahntechn. Rundschau ETR, 39(7/8), 465–468 (1990)

    Google Scholar 

  25. Carey, M., Kwiecinski, A.: Stochastic approximation to the effects of headways on knock-on delays of trains. Transp. Res. Part B 28(4), 251–267 (1994)

    Article  Google Scholar 

  26. Goverde, R.M.P.: Punctuality of Railway Operations and Timetable Stability Analysis: PhD thesis - Technical University of Delft, 165 p (2005)

    Google Scholar 

  27. Mazzarello, M., Ottaviani, E.: A traffic management system for real-time traffic optimazation in railways. Transp. Res. Part B 41(2), 246–274 (2007)

    Article  Google Scholar 

  28. Mes, M., van der Heijden, A., van Harten, N.: Comparison of agent-based scheduling to look-ahead heuristics for real-time transportation problems. Eur. J. Oper. Res. 181(1), 59–75 (2007)

    Article  MathSciNet  Google Scholar 

  29. Davydov, B.I., Kotlyarova, E.V., Davydov, B.I.: EHkonomicheskoe obosnovanie racional’noj skorosti dvizheniya poezdov: EHkonomika zheleznyh dorog, vol. 4, S.17–23 (2008)

    Google Scholar 

  30. Kovalev, A.P.: Ocenka nadezhnosti grafika i skorosti dvizheniya pas-sazhirskih poezdov: ZHeleznod. transport, vol. 5, S.42–45 (2006)

    Google Scholar 

  31. Mazo, L.A., Mikul’skij, A.A.: Pokazateli ispol’zovaniya perevozochnyh resursov [Tekst]: Mir transporta, vol. 2, S. 66–73 (2008)

    Google Scholar 

  32. Gapanenok, V.I., ZHabrov, S.S., Popov, Y.V.: EHkonomika grafika: ZHeleznodorozhnyj transport, vol. 5, S. 24–28 (2006)

    Google Scholar 

  33. Karchik, V.G., Pershin, I.V., YUrkova, E.A.: Processnyj podhod k rabote uchastkovoj stancii [Tekst]: EHkonomika zheleznyh dorog, vol. 11. – S. 24–39 (2009)

    Google Scholar 

  34. Bent, R., Van Hentenryck, P.: The value of consensus in online stochastic scheduling [Text]. In: Proceedings of the ICAPS, pp. 219–226 (2004)

    Google Scholar 

  35. Ventcel’ E.S., Ovcharov, L.A., Vysshaya shkola, M.: Teoriya veroyatnostej i ee inzhenernye prilozheniya, 480 s (2000)

    Google Scholar 

  36. Borovkov A.A.: Teoriya veroyatnostej: Ucheb. posobie dlya vuzov. – 2-e izd., pererab. i dop.: Nauka, 432 s (1986)

    Google Scholar 

  37. Ventcel’, E.S.: Teoriya veroyatnostej: Nauka, 576 s (1969)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Far Eastern State Transport University, Khabarovsk, 680000, Russian Federation

    Boris Davydov & Vadim Gopkalo

  2. JST Russian Railways, Far Eastern Branch, Khabarovsk, 680000, Russian Federation

    Vyacheclav Esaulov

  3. Computer Center FEB RAS, Khabarovsk, 680000, Russian Federation

    Kseniya Kablukova

Authors
  1. Boris Davydov
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  2. Vyacheclav Esaulov
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  3. Vadim Gopkalo
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  4. Kseniya Kablukova
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Corresponding author

Correspondence to Vadim Gopkalo .

Editor information

Editors and Affiliations

  1. Covenant University, Ota, Nigeria

    Sanjay Misra

  2. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  3. University of Basilicata, Potenza, Italy

    Beniamino Murgante

  4. Saint Petersburg State University, Saint Petersburg, Russia

    Elena Stankova

  5. Saint Petersburg State University, Saint Petersburg, Russia

    Vladimir Korkhov

  6. Polytechnic University of Bari, Bari, Italy

    Carmelo Torre

  7. University of Minho, Braga, Portugal

    Ana Maria A.C. Rocha

  8. Monash University, Clayton, VIC, Australia

    David Taniar

  9. Kyushu Sangyo University, Fukuoka, Japan

    Bernady O. Apduhan

  10. Polytechnic University of Bari, Bari, Italy

    Eufemia Tarantino

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Davydov, B., Esaulov, V., Gopkalo, V., Kablukova, K. (2019). Basic Framework for Adjusting the Freight Train Schedule. In: Misra, S., et al. Computational Science and Its Applications – ICCSA 2019. ICCSA 2019. Lecture Notes in Computer Science(), vol 11620. Springer, Cham. https://doi.org/10.1007/978-3-030-24296-1_15

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  • DOI: https://doi.org/10.1007/978-3-030-24296-1_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-24295-4

  • Online ISBN: 978-3-030-24296-1

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