Skip to main content

A Decision Method for Disruption Management Problems in Intermodal Freight Transport

  • Conference paper
Intelligent Decision Technologies

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 10))

Abstract

In this paper, we propose a new decision method for dealing with disruption events in intermodal freight transport. First of all, the forecasting decision for the duration of disruption events is presented, which decides whether a rearrangement is needed. Secondly, a network-based optimization model for intermodal freight transport disruption management is built. Then an improved depth-first search strategy is developed, which is beneficial to automatically generating the routes and achieving the recovery strategies quickly. Finally, a numerical example is applied to verify the decision method. The new decision method supports the real-time decision making for disruption management problems.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Arnold, P., Peeters, D., Thomas, I.: Modelling a rail/road intermodal transportation system. Transportation Research Part E 40(3), 255–270 (2004)

    Article  Google Scholar 

  2. Campbell, J., Ernst, A., Krishnamoorthy, M.: Hub location problems. In: Drezner, Z., Hamacher, H. (eds.) Facility location: Applications and theory. Springer, Heidelberg (2002)

    Google Scholar 

  3. Caris, A., Macharis, C., Janssens, G.K.: Planning problems in intermodal freight transport: accomplishments and prospects. Transportation Planning and Technology 31(3), 277–302 (2008)

    Article  Google Scholar 

  4. Chang, T.S.: Best routes selection in international intermodal networks. Computers & operations research 35(9), 2877–2891 (2008)

    Article  MATH  Google Scholar 

  5. Crainic, T.G., Kim, K.H.: Intermodal transportation. In: Laporte, G., Barnhart, C. (eds.) Handbooks in Operations Research & Management Science: Transportation. Elsevier, Amsterdam (2007)

    Google Scholar 

  6. Du, T.C., Li, E.Y., Chou, D.: Dynamic vehicle routing for online B2C delivery. Omega 33(1), 33–45 (2005)

    Article  Google Scholar 

  7. Huang, L.F., Wang, L.L.: An analysis of selecting the intermodal transportation routes. Logistics Engineering and Management 32(187), 4–6 (2010)

    Google Scholar 

  8. Huisman, D., Freling, R., Wagelmans, A.P.M.: A robust solution approach to the dynamic vehicle scheduling problem. Transportation Science 38(4), 447–458 (2004)

    Article  Google Scholar 

  9. Li, J.Q., Borenstein, D., Mirchandani, P.B.: A decision support system for the single-depot vehicle rescheduling problem. Computers & Operations Research 34(4), 1008–1032 (2007)

    Article  MATH  Google Scholar 

  10. Li, J.Q., Mirchandani, P.B., Borenstein, D.: A Lagrangian heuristic for the real-time vehicle rescheduling problem. Transportation Research Part E 45(3), 419–433 (2009)

    Article  MathSciNet  Google Scholar 

  11. Liu, J., Yu, J.N.: Optimization model and algorithm on transportation mode selection in intermodal networks. Journal of Lanzhou Jiaotong University 29(1), 56–61 (2010)

    Google Scholar 

  12. Liu, J., Yu, J.N., Dong, P.: Optimization model and algorithm for intermodal carrier selection in various sections. Operations Research and Management Science 19(5), 160–166 (2010)

    MATH  Google Scholar 

  13. Liu, W.M., Guan, L.P., Yin, X.Y.: Prediction of freeway incident duration based on decision tree. China Journal of Highway and Transport 18(1), 99–103 (2005)

    Google Scholar 

  14. Macharis, C., Bontekoning, Y.M.: Opportunities for OR in intermodal freight transport research: A review. European Journal of Operational Research 153(2), 400–416 (2004)

    Article  MATH  Google Scholar 

  15. Macharis, C., Bontekoning, Y.M.: Opportunities for OR in intermodal freight transport research: a review. European Journal of Operational Research 153(2), 400–416 (2004)

    Article  MATH  Google Scholar 

  16. Ma, C.W.: Carrier selection in various sections of multi-modal transport based on multi-Agent. Journal of Harbin Institute of Technology 39(12), 1989–1992 (2007)

    Google Scholar 

  17. Meng, Q., Wang, X.C.: Intermodal hub-and-spoke network design: Incorporating multiple stakeholders and multi-type containers. Transportation Research Part B (2010), doi:10.1016/j.trb.2010.11.002

    Google Scholar 

  18. Potivn, J.Y., Ying, X., Benyahia, I.: Vehicle routing and scheduling with dynamic travel times. Computers & Operations Research 33(4), 1129–1137 (2006)

    Article  Google Scholar 

  19. Shinghal, N., Fowkes, T.: Freight model choice and adaptive stated preferences. Transportation Research Part E 38(5), 367–378 (2002)

    Article  Google Scholar 

  20. Sirikijpanichkul, A., Van Dam, H., Ferreira, L., Lukszo, Z.: Optimizing the Location of Intermodal Freight Hubs: An overview of the agent based modelling approach. Journal of Transportation Systems Engineering and Information Technology 7(4), 71–81 (2007)

    Article  Google Scholar 

  21. Taniguchi, E., Shimamoto, H.: Intelligent transportation system based dynamic vehicle routing and scheduling with variable travel times. Transportation Research Part C 12(3-4), 235–250 (2004)

    Article  Google Scholar 

  22. Wang, X.P., Xu, C.L., Yang, D.L.: Disruption management for vehicle routing problem with the request changes of customers. International Journal of Innovative, Information and Control 5(8), 2427–2438 (2009)

    Google Scholar 

  23. Yang, X.J., Low, J.M.W., Tang, L.C.: Analysis of intermodal freight from China to Indian Ocean: A goal programming approach. Journal of Transport Geography (2010), doi:10.1016/j.jtrangeo.2010.05.007

    Google Scholar 

  24. Zeimpekis, V., Giaglis, G.M., Minis, I.: A dynamic real-time fleet management system for incident handling in city logistics. In: 2005 IEEE 61st Vehicular Technology Conference, pp. 2900–2904 (2005)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Huang, M., Hu, X., Zhang, L. (2011). A Decision Method for Disruption Management Problems in Intermodal Freight Transport. In: Watada, J., Phillips-Wren, G., Jain, L.C., Howlett, R.J. (eds) Intelligent Decision Technologies. Smart Innovation, Systems and Technologies, vol 10. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22194-1_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-22194-1_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22193-4

  • Online ISBN: 978-3-642-22194-1

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics