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Coordination of locomotives turnover and servicing modes

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
A coordinated calculation of two processes – locomotives turnover and servicing – is described. Locomotives turnover is calculated by optimization system Labyrinth and servicing by dynamic transportation problem. Service programs integrate these processes. A model of coordinated arrival of locomotives at servicing stations is proposed. The calculation consists of three interrelated steps. The first step is the calculation of the optimal locomotive turnover without considering servicing constraints. Service program SP-1 determines stations where forced stops will take place according to the necessity of servicing and forms the basic location of locomotives for further movement to servicing stations. The second step is the calculation of the optimal arrival of locomotives at servicing stations. Service program SP-2 provides location and release time of each locomotive after servicing. The third step is the calculation of a train schedule with the consideration for the location of stopped train sets and the appearance of locomotives after servicing. Servicing program SP-3 forms the united results.
Czasopismo
Rocznik
Strony
19--26
Opis fizyczny
Bibliogr. 18 poz.
Twórcy
autor
  • Research and Production Holding STRATEG Nizhegorodskaya 32, building 15, 109029, Moscow, Russia
autor
  • Ural State University of Railway Transport Kolmogorova 66, 620034, Ekaterinburg, Russia
autor
  • Ural State University of Railway Transport Kolmogorova 66, 620034, Ekaterinburg, Russia
Bibliografia
  • 1. Козлов, П.А. & Вакуленко, С.П. Расчет оптимальных режимов работы локомотивов при обслуживании поездопотоков. Транспорт Урала. 2015. No 1. P.3-8. [In Russian: Kozlov, P.A. & Vakulenko, S.P. Calculation of the optimal locomotives work modes at servicing train flows. Ural Transport].
  • 2. Козлов, П.А. & Вакуленко, С.П. Оптимизация режимов работы локомотивов с помощью системы Лабиринт. Миртранспорта. 2016. No 4. P.10-14. [In Russian: Kozlov, P.A., Vakulenko, S.P. Optimization of locomotive work modes with the use of system Labyrinth. World of Transport and Transportation].
  • 3. Козлов, П.А. & Вакуленко, С.П. Оптимизация оборота локомотивов при заданных поездопотоках. Железнодорожный транспорт. 2016. No 10. P. 34-37. [In Russian: Kozlov, P.A. & Vakulenko, S.P. Optimization of locomotives turnover for given train flows. Railway Transport].
  • 4. Козлов, П.А. & Миловидов, С.П. Оптимизация структуры транспортных потоков в динамике при приоритете потребителей. Экономикаиматематическиеметоды. 1982. Vol. XVIII. No. 3. P. 521-531. [In Russian: Kozlov P.A. & Milovidov C.P. Optimization of the traffic flows in dynamics and in the conditions of consumers’ priority. Economics and mathematical methods].
  • 5. Booler, J.M.P. The solution of a railway locomotive scheduling problem. Journal of the Operational Research Society. 1980. No. 31. P. 943-948.
  • 6. Wright, M. B. Applying stochastic algorithms to a locomotive scheduling problem. Journal of the Operational Research Society. 1989. No. 40. P. 187-192.
  • 7. Ziarati, K. & Soumis, F. & Desrosiers, J. & Solomon, M.M. A branch-first, cut-second approach for locomotive assignment. Management Science. 1999. No. 45. P. 1156-1168.
  • 8. Cordeau, J.F. & Soumis, F. & Desrosiers, J. A benders decomposition approach for the locomotive and car assignment problem. Transportation Science. 2000. No. 34. P. 133-149.
  • 9. Ahuja, R.K. & Liu, J. & Orlin, J.B. & Sharma, D. & Shughart, L. A. Solving real-life locomotive scheduling problems. Transportation Science. 2005. No. 39. P. 503-517.
  • 10. Powell, W.B. & Shapiro, J.A. & Simao, H.P. An adaptive dynamic programming algorithm for the heterogeneous resource allocation problem. Transportation Science. 2002. No. 36. P. 231-249.
  • 11. Powell, W.B. & Topaloglu, H. Stochastic programming in transportation and logistics. Handbooks in Operations Research and Management Science. 2003. No. 10. P. 55-636.
  • 12. Powell, W.B. Dynamic models of transportation operations. Handbooks in Operations Research and Management Science. 2003. No. 11. P. 677-756.
  • 13. Powell, W.B. & Topaloglu, H. Fleet management. Applications of Stochastic Programming. 2005. P. 185-215.
  • 14. Topaloglu, H. & Powell, W.B. Dynamic-programming approximations for stochastic time-staged integer multicommodity-flow problems. INFORMS Journal on Computing. 2006. No. 18. P. 31.
  • 15. Maroti, G. & Kroon, L. Maintenance routing for train units: the transition model. Transportation Science. 2005. No. 39. P. 518-525.
  • 16. Vaidyanathan, B. & Ahuja, R.K. & Orlin, J.B. The locomotive routing problem. Transportation Science. 2008. No. 42. P. 492-507.
  • 17. Powell, W. & Bouzaiene-Ayari, B. & Cheng, C. & Fiorillo, R. & Das, S. & Lawrence, C. Strategic, tactical and real-time planning of locomotives at Norfolk Southern using approximate dynamic programming. In: Joint Rail Conference. Philadelphia, Pennsylvania, USA, April 17–19, 2012. Paper No. JRC2012-74187. P. 491-500
  • 18. Козлов, П.А. Теоретические основы, организационные формы, методы оптимизации гибкой технологии транспортного обслуживания заводов черной металлургии. DSc thesis. Липецк: ЛПИ. 1986. 377 p. [In Russian: Kozlov, P.A. Theoretical basis, organizational forms, methods to optimize the flexible technology of the ferrous industry transportation service. DSc thesis. Lipetsk: LPI].
Uwagi
PL
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-60479a7d-c55c-4733-8aa3-3876d1802113
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