An improved method of determining the schemes of locomotive circulation with regard to the technological peculiarities of railcar traffic

Authors

  • Tatyana Butko Ukrainian State University of Railway Transport Feuerbach sq., 7, Kharkiv, Ukraine, 61166, Ukraine
  • Andrii Prokhorchenko Ukrainian State University of Railway Transport Feuerbach sq., 7, Kharkiv, Ukraine, 61166, Ukraine https://orcid.org/0000-0003-3123-5024
  • Mykhailo Muzykin Dnipropetrovsk National University of Railway Transport named after academician V. Lazaryan Ac. Lazaryana str., 2, Dnipro, Ukraine, 49010, Ukraine https://orcid.org/0000-0003-2938-7061

DOI:

https://doi.org/10.15587/1729-4061.2016.80471

Keywords:

railway network, railcar traffic, locomotive planning, locomotive crew, genetic algorithm

Abstract

This paper focuses on new analytical solutions in the area of building locomotives’ circulation plans to handle individual applications for route transportation of freight. Such a domain has been little researched for the railway network of Ukraine, whereas the present study provides a basis for automating the planning process. The main aim is to improve the methods of determining the schemes of locomotives’ turnover in the railway network of Ukraine under the condition of an accelerated handling of individual railcar traffic and with regard to technological peculiarities. The developed mathematical model simultaneously makes it possible to determine the weight of trains on the routes they follow, to outline the circuity of locomotives with regard to deploying various series of locomotives within the network, and to regulate the system of locomotive crews’ operations in view of the existing technical and technological features of locomotive facilities and the railway infrastructure. The suggested mathematical model is processed in the study through the use of an integer genetic algorithm with its own system of coding the solution. The results have confirmed the adequacy of the developed mathematical model. The use of the suggested mathematical model on the basis of the genetic algorithm can help automate the complex process of determining the schemes of locomotives’ circulation with regard to the technological peculiarities of railcar traffic and, consequently, improve the accuracy and speed of decision-making for servicing individual applications for route transportation of freight.

Author Biographies

Tatyana Butko, Ukrainian State University of Railway Transport Feuerbach sq., 7, Kharkiv, Ukraine, 61166

Doctor of Engineering, Professor

Department of Operational Work Management

Andrii Prokhorchenko, Ukrainian State University of Railway Transport Feuerbach sq., 7, Kharkiv, Ukraine, 61166

PhD, associate professor

Department of Operational Work Management

Mykhailo Muzykin, Dnipropetrovsk National University of Railway Transport named after academician V. Lazaryan Ac. Lazaryana str., 2, Dnipro, Ukraine, 49010

Assistant

Department of Life safety

References

  1. Lomotko, D. V., Alyoshinsky, E. S., Zambrybor, G. G. (2016). Methodological Aspect of the Logistics Technologies Formation in Reforming Processes on the Railways. Transportation Research Procedia, 14, 2762–2766. doi: 10.1016/j.trpro.2016.05.482
  2. Stratehiya dlya tyahy. Vseukrayins'ka zaliznychna hazeta Mahistral' 2-8 veresnya 2015 r. # 67 (2056). Available at: http://www.magistral-uz.com.ua/file/696.pdf
  3. Kozachenko, D. N., Berezovyj, N. I., Vernigora, R. V. (2014). Problemy dopuska sobstvennyh lokomotivov na magistral'nuyu zheleznodorozhnuyu іnfrastrukturu. Problemy ehkonomiki i upravleniya na zheleznodorozhnom transporte, 9, 243–246.
  4. Yel'nikova, L. O. (2016). Pidvyshchennya efektyvnosti pereviznoho protsesu na zaliznychnykh napryamkakh za rakhunok udoskonalennya operatyvnoho keruvannya ekspluatatsiyeyu lokomotyvnoho parku. D., 182.
  5. Kornienko, V. V., Kotel'nikov, A. V., Domanskij EHnergeticheskaya, V. T. (2010). Bezopasnost' zheleznyh dorog i strategiya ih razvitiya. Zalіznichnij transport Ukraini, 6, 5–9.
  6. But'ko, T. V., Lomot'ko, D. V., Prokhorchenko, A. V., Oliynyk, K. O. (2009). Formuvannya lohistychnoyi tekhnolohiyi prosuvannya vantazhopotokiv za zhorstkymy nytkamy hrafiku rukhu poyizdiv. Zbirnyk naukovykh prats', 78, 71–75.
  7. Zhukovytskyi, I. V., Skalozub, V. V, Vetrova, O. V., Zinenko, O. L. (2006). Modeling of the operational planning process of working locomotives and locomotive crews. Science and Transport Progress. Bulletin of Dnipropetrovsk National University of Railway Transport, 12, 74–78.
  8. Vernyhora, R. V., Yel'nikova, L. O. (2012). Perspektyvy stvorennya adaptyvnoyi systemy operatyvnoho keruvannya robotoyu lokomotyviv ta lokomotyvnykh bryhad. Transportni systemy i tekhnolohiyi perevezen', 4, 25–29.
  9. Instruktsiya zi skladannya hrafika rukhu poyizdiv na zaliznytsyakh Ukrayiny (2002). TsD-0040. Zatv.Ukrzaliznytsya 05.04.2002. Vyd.ofits. Kyiv: Transport Ukrayiny, 164.
  10. Nekrashevich, V. I., Ignatov, A. I. (2008). Teoreticheskie aspekty vybora vesovyh norm sostavov gruzovyh poezdov i sistemy tyagovogo obsluzhivaniya napravlenij. Sbornik nauchnyh trudov Ros. gos. otkr. tekhn. un-t putej soobshcheniya, 8, 98–106.
  11. Anikina, O. V. (2001). Sovershenstvovanie metodov ehkspluatacii magistral'nyh lokomotivov gruzovogo dvizheniya v usloviyah sozdaniya novoj modeli upravleniya perevozochnym processom. Nsk., 176.
  12. Kapustin, N. I. (2007). Kompleksnaya optimizaciya parametrov tyagovogo obespecheniya gruzovyh poezdov na poligone seti zheleznyh dorog. Moscow, 182.
  13. Kozlov, P. A., Vakulenko, S. P. (2015). Model' optimal'nogo grafika oborota poezdnyh loko-motivov. Vestnik VNIIZHT, 2, 15–20.
  14. Vaidyanathan, B., Ahuja, R. K., Orlin, J. B. (2008). The Locomotive Routing Problem. Transportation Science, 42 (4), 492–507. doi: 10.1287/trsc.1080.0244
  15. Mellouli, T., Suhl, L. (2007). Rotation Planning of Locomotive and Carriage Groups with Shared Capacities. Algorithmic Methods for Railway Optimization, 4359, 276–294. doi: 10.1007/978-3-540-74247-0_15
  16. Ahuja, R. K., Liu, J., Orlin, J. B., Sharma, D., Shughart, L. A. (2005). Solving Real-Life Locomotive-Scheduling Problems. Transportation Science, 39 (4), 503–517. doi: 10.1287/trsc.1050.0115
  17. Ziarati, K., Nezhad, A. M. (2004). Cyclic locomotive assignment problem using Ising mean field technique. Ferdowsi University of Mashad, 3, 98–103.
  18. Ziarati, K., Soumis, F., Desrosiers, J., Gélinas, S., Saintonge, A. (1997). Locomotive assignment with heterogeneous consists at CN North America. European Journal of Operational Research, 97 (2), 281–292. doi: 10.1016/s0377-2217(96)00198-1
  19. Teichmann, D., Dorda, M., Golc, K., Bínová, H. (2015). Locomotive Assignment Problem with Heterogeneous Vehicle Fleet and Hiring External Locomotives. Mathematical Problems in Engineering, 2015, 1–7. doi: 10.1155/2015/583909
  20. Noori, S., Ghannadpour, S. F. (2012). Locomotive Assignment problem with trains precedence using genetic algorithm. Journal of Industrial Engineering International, 8 (1), 9. doi: 10.1186/2251-712x-8-9
  21. Ghoseiri, K., Ghannadpour, S. F. (2010). A hybrid genetic algorithm for multi-depot homogenous locomotive assignment with time windows. Applied Soft Computing, 10 (1), 53–65. doi: 10.1016/j.asoc.2009.06.004
  22. Aksoy, A., Altan, A. (2013). The integrated Locomotive Assigment and Crew Scheduling Problem. International Journal of Computational Engineering Research, 3, 18–24.
  23. Godwin, T., Gopalan, R., Narendran, T. T. (2006). Locomotive assignment and freight train scheduling using genetic algorithms. International Transactions in Operational Research, 13 (4), 299–332. doi: 10.1111/j.1475-3995.2006.00550.x
  24. Vernigora, R. V., El'nikova, L. O. (2015). Problemy operativnogo planirovaniya raboty lokomotivnogo parka Ukrainy v sovremennyh usloviyah i puti ih resheniya. Nauka i transport, 2 (31), 120–125.
  25. Tihonov, K. K. (1962). Tekhniko-ehkonomicheskie raschety v ehkspluatacii zheleznyh dorog. Moscow: Transport, 252.
  26. Panchenko, S., Butko, T., Prokhorenko, A., Parkhomenko, L. (2016). Formation of an automated traffic capacity calculation system of rail networks for freight flows of mining and smelting enterprises. Naukovyi Visnyk, 2, 93–99.
  27. Ren, Z.-G., Feng, Z.-R., Ke, L.-J., Zhang, Z.-J. (2010). New ideas for applying ant colony optimization to the set covering problem. Computers & Industrial Engineering, 58 (4), 774–784. doi: 10.1016/j.cie.2010.02.011
  28. Karp, R. M. (1972). Reducibility among Combinatorial Problems. Complexity of Computer Computations, 85–103. doi: 10.1007/978-1-4684-2001-2_9
  29. Rutkovskaya, D., Pilinskij, M., Rutkovskij, L. (2004). Nejronnye seti, geneticheskie algoritmy i nechetkie sistemy. Moscow: Goryachaya liniya, 452.
  30. Panchenko, T. V. (2007). Geneticheskie algoritmy. Ast: Izdatel'skij dom «Astrahanskij universitet», 87.
  31. Beasley, J. E., Chu, P. C. (1996). A genetic algorithm for the set covering problem. European Journal of Operational Research, 94 (2), 392–404. doi: 10.1016/0377-2217(95)00159-x
  32. Aickelin, U. (2002). An indirect genetic algorithm for set covering problems. Journal of the Operational Research Society, 53 (10), 1118–1126. doi: 10.1057/palgrave.jors.2601317
  33. Powell, W. B., Bouzaiene-Ayari, B., Lawrence, C., Cheng, C., Das, S., Fiorillo, R. (2014). Locomotive Planning at Norfolk Southern: An Optimizing Simulator Using Approximate Dynamic Programming. Interfaces, 44 (6), 567–578. doi: 10.1287/inte.2014.0741

Downloads

Published

2016-10-30

How to Cite

Butko, T., Prokhorchenko, A., & Muzykin, M. (2016). An improved method of determining the schemes of locomotive circulation with regard to the technological peculiarities of railcar traffic. Eastern-European Journal of Enterprise Technologies, 5(3 (83), 47–55. https://doi.org/10.15587/1729-4061.2016.80471

Issue

Vol. 5 No. 3 (83) (2016): Control processes

Section

Control processes

License

Copyright (c) 2016 Тетяна Василівна Бутько, Andrii Prokhorchenko, Mykhailo Muzykin

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

The consolidation and conditions for the transfer of copyright (identification of authorship) is carried out in the License Agreement. In particular, the authors reserve the right to the authorship of their manuscript and transfer the first publication of this work to the journal under the terms of the Creative Commons CC BY license. At the same time, they have the right to conclude on their own additional agreements concerning the non-exclusive distribution of the work in the form in which it was published by this journal, but provided that the link to the first publication of the article in this journal is preserved.

A license agreement is a document in which the author warrants that he/she owns all copyright for the work (manuscript, article, etc.).
The authors, signing the License Agreement with TECHNOLOGY CENTER PC, have all rights to the further use of their work, provided that they link to our edition in which the work was published.
According to the terms of the License Agreement, the Publisher TECHNOLOGY CENTER PC does not take away your copyrights and receives permission from the authors to use and dissemination of the publication through the world's scientific resources (own electronic resources, scientometric databases, repositories, libraries, etc.).
In the absence of a signed License Agreement or in the absence of this agreement of identifiers allowing to identify the identity of the author, the editors have no right to work with the manuscript.
It is important to remember that there is another type of agreement between authors and publishers – when copyright is transferred from the authors to the publisher. In this case, the authors lose ownership of their work and may not use it in any way.