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Carrying capacity and efficiency optimization model for freight train segment train

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Abstract

With economic expansion having moderated to a “new normal” pace, supply structure of goods and competition state of logistics market has undergone major changes. In order to respond to these changes actively, China Railway Corporation has launched railway express freight block trains to meet with customers’ demands. However, traditional operation conditions require every freight block train fully loaded to make best of transportation capacity. This has caused a series of problems to freight block trains, such as uncertain departure time, unstable running frequency and so on, which cannot meet with the customers’ basic requirements for goods transport and logistics. So it is an urgent task to study the suitable cars’ number and running frequency of railway express freight block trains so as to reduce customers’ costs and increase China Railway Corporation’s profits. Therefore, this paper analyzes the calculation method of customers’ generalized transportation cost and profits of running a railway express freight block train. Then, an optimization model for cars’ number and running frequency of freight block trains is proposed. The objective functions of this model are the minimum general transportation costs of customers and the maximum profits of China Railway Corporation. The model constraints are about transportation capacity, railway freight stations’ operating capacity and so on. Taking railway express freight block trains operated between Beijing and Shanghai as an example, the cars’ number and running frequency are calculated which can effectively reduce customers’ cost and increase China Railway Corporation’s profits. The results can prove the feasibility of the model proposed in this paper.

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References

  1. Kaspi, M., Raviv, T.: Service-oriented line planning and timetabling for passenger trains. Transp. Sci. 47(3), 295–311 (2013)

    Google Scholar 

  2. Shi, R.J., Mao, B.H., Ding, Y., Bai, Y., Chen, Y.: Timetable optimization of rail transit loop line with transfer coordination. Discret. Dyn. Nat. Soc. (2016). https://doi.org/10.1155/2016/4627094

    MathSciNet  Google Scholar 

  3. Ke, B.R., Lin, C.L., Chien, H.H., Chiu, H.W., Chen, N.: A new approach for improving the performance of freight train timetabling of a single-track railway system. Transp. Plan. Technol. 38(2), 238–264 (2015)

    Google Scholar 

  4. Khobotov, E.N., Tarasov, M.A., Shavin, M.Y., Kuznetsova, A.Y.: On one approach to constructing timetables of freight trains in a railroad network. Autom. Remote Control 77(11), 2006–2017 (2016)

    MathSciNet  MATH  Google Scholar 

  5. Lawley, M., Parmeshwaran, V., Richard, J.P., Turkcan, A., Dalal, M.: A time–space scheduling model for optimizing recurring bulk railcar deliveries. Transp. Research Part B 42(5), 438–454 (2008)

    Google Scholar 

  6. Fumasoli, T., Bruckmann, D., Weidmann, U., Dresner, M.: Operation of freight railways in densely used mixed traffic networks—an impact model to quantify changes in freight train characteristics. Res. Transp. Econ. 54, 15–19 (2015)

    Google Scholar 

  7. Cacchiani, V., Caprara, A., Toth, P.: Scheduling extra freight trains on railway networks. Transp. Res. Part B 44(2), 215–231 (2010)

    Google Scholar 

  8. Andersen, J., Crainic, T.G., Christiansen, M.: Service network design with management and coordination of multiple fleets. Eur. J. Oper. Res. 193(2), 377–389 (2009)

    MathSciNet  MATH  Google Scholar 

  9. Atanassov, I., Dick, C.T.: Capacity of single-track railway lines with short sidings to support operation of long freight trains. Transp. Res. Rec. 2475, 95–101 (2015)

    Google Scholar 

  10. Upadhyay, A., Bolia, N.: Combined empty and loaded train scheduling for dedicated freight railway corridors. Comput. Ind. Eng. 76, 23–31 (2014)

    Google Scholar 

  11. Ahuja, R.K., Jha, K.C., Liu, J.: Solving real-life railroad blocking problems. Interfaces 37(5), 404–419 (2007)

    Google Scholar 

  12. Zhang, Y., Yan, Y.: An operation optimization for express freight trains based on shipper demands”. Discret. Dyn. Nat. Soc. (2014). https://doi.org/10.1155/2014/232890

    MathSciNet  MATH  Google Scholar 

  13. Lin, B.L., Wang, Z.M., Ji, L.J., Tian, Y.M., Zhou, G.Q.: Optimizing the freight train connection service network of a large-scale rail system. Transp. Res. Part B 46(5), 649–667 (2012)

    Google Scholar 

  14. Jonaitis, J.: Planning of the amount of trains needed for transportation by rail. Transport 22(2), 83–89 (2010)

    Google Scholar 

  15. Mancuso, P., Reverberi, P.: Operating costs and market organization in railway services. The case of Italy, 1980–1995. Transp. Res. Part B 37(1), 43–61 (2003)

    Google Scholar 

  16. Cohn, A., Davey, M., Schkade, L., Siegel, A., Wong, C.: Network design and flow problems with cross-arc costs. Eur. J. Oper. Res. 189(3), 890–901 (2008)

    MATH  Google Scholar 

  17. Borndörfer, R., Klug, T., Schlechte, T., Fügenschuh, A., Schang, T.: The freight train routing problem for congested railway networks with mixed traffic. Transp. Sci. 50(2), 408–423 (2016)

    Google Scholar 

  18. Khaled, A.A., Jin, M., Clarke, D.B., Hoque, M.A.: Train design and routing optimization for evaluating criticality of freight railroad infrastructures. Transp. Res. Part B 71, 71–84 (2015)

    Google Scholar 

  19. Deng, Y., Tong, H.: Dynamic shortest path algorithm in stochastic traffic networks ssing PSO based on fluid neural network. J. Intell. Learn. Syst. Appl. 3(3), 11–16 (2011)

    Google Scholar 

  20. Cohn, A., Root, S., Wang, A., Mohr, D.: Integration of the load-matching and routing problem with equipment balancing for small package carriers. Transp. Sci. 41(2), 238–252 (2007)

    Google Scholar 

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Acknowledgements

The study is financially supported Scientific Research Project from National Railway Administration of P.R.C. (T17DJ00030), Projects for Science and Technology from China Railway Corporation (2016X007-B), Scientific Research Project from Standardization Administration of P.R.C. (No. 201510210-03).

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Correspondence to Pei Wang.

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The authors declare that they do not have any commercial or associative interests that represent a conflict of interests in connection with this work.

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Wang, P., Zhang, X., Han, B. et al. Carrying capacity and efficiency optimization model for freight train segment train. Cluster Comput 22 (Suppl 2), 4927–4940 (2019). https://doi.org/10.1007/s10586-018-2444-0

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  • DOI: https://doi.org/10.1007/s10586-018-2444-0

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