Skip to main content
Log in

An Analysis of Exact VRPTW Solutions on ITS Data-based Logistics Instances

  • Published:
International Journal of Intelligent Transportation Systems Research Aims and scope Submit manuscript

Abstract

This paper describes an exact solution approach for the Vehicle Routing and scheduling Problem with Soft Time Windows (VRPSTW), and presents its application on a realistic logistics instance based on the VICS (Vehicle Information and Communication System) data, an ITS application in Japan. Exact solutions of VRPSTW have been compared with those of the Vehicle Routing and scheduling with Hard Time Windows (VRPHTW). Detailed analysis of environmental issues and idling time along with the traditional comparison of cost and number of vehicles, shows that the exact VRPSTW solutions are not only cost efficient but helpful in reducing congestion, which implies these are more environmentally sustainable.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

References

  1. Ortuzar, J.D., Willumsen, L.G.: Modeling Transport. Wiley, England (1995)

    Google Scholar 

  2. Thompson, R.G., Taniguchi, E.: City logistics and freight transport. In: Brewer, A.M., Button, K.J., Hensher, D.A. (eds.) Handbook of Logistics and Supply–Chain Management, pp. 393–405. Pergamon, Oxford (2001)

    Google Scholar 

  3. van JHR, Duin, Tavasszy, L.A., Taniguchi, E.: Real time simulation of auctioning and re-scheduling process in hybrid freight markets. Transportation Research Part B 41, 1050–1066 (2007)

    Article  Google Scholar 

  4. Solomon, M.M.: Algorithms for the vehicle routing and scheduling problem with time windows constraints. Oper. Res. 35(2), 254–265 (1987)

    Article  Google Scholar 

  5. Thompson, R.G., Van Duin, J.H.R.: Vehicle routing and scheduling. In: Taniguchi, E., Thompson, R.G. (eds.) Innovations in Freight Transport, pp. 47–63. WIT Press, Southampton (2003)

    Google Scholar 

  6. Taillard, E., Badeau, P., Guertin, F., Gendreau, M., Potvin, J.: A tabu search heuristic for the vehicle routing problem with soft time windows. Transp. Sci. 31, 170–186 (1997)

    Article  MATH  Google Scholar 

  7. Gendreau, M., Guertin, F., Potvin, J., Taillard, E.: Parallel tabu search for real-time vehicle and dispatching. Transp. Sci. 33, 381–390 (1999)

    Article  MATH  Google Scholar 

  8. Taniguchi, E., Thompson, R.G.: Modeling city logistics. Transport. Res. Rec. 1790, 45–51 (2002)

    Article  Google Scholar 

  9. Qureshi, A., Hanaoka, S.: Analysis of the effects of cooperative delivery system in Bangkok. In: Taniguchi, E., Thompson, R.G. (eds.) Recent Advances in City Logistics, pp. 59–73. Elsevier, Oxford (2005)

    Google Scholar 

  10. Yamada, T., Taniguchi, E., Itoh, Y.: Co-operative vehicle routing model with optimal location of logistics terminals. In: Taniguchi, E., Thompson, R.G. (eds.) City Logistics II, pp. 139–153. Institute for City Logistics, Japan (2001)

    Google Scholar 

  11. Kolen, A.W.J., Rinnooy Kan, A.H.G., Trienekens, H.W.J.M.: Vehicle routing with time windows. Oper. Res. 35, 266–273 (1987)

    Article  MATH  MathSciNet  Google Scholar 

  12. Kallehauge, B., Larsen, J., Madsen, O.B.G.: Lagrangian duality applied to the vehicle routing problem with time windows. Comput. Oper. Res. 33, 1464–1487 (2006)

    Google Scholar 

  13. Kohl, N., Madsen, O.B.G.: An optimization algorithm for the vehicle routing problem with time windows based on Lagrangian relaxation. Oper. Res. 45, 395–406 (1997)

    Article  MATH  MathSciNet  Google Scholar 

  14. Desrochers, M., Desrosiers, J., Solomon, M.: A new optimization algorithm for the vehicle routing problem with time windows. Oper. Res. 40, 342–354 (1992)

    Article  MATH  MathSciNet  Google Scholar 

  15. Feillet, D., Dejax, P., Gendreau, M., Gueguen, C.: An exact algorithm for the elementary shortest path problem with resource constraints: application to some vehicle routing problems. Networks, 216–229 (2004)

  16. Chabrier, A.: Vehicle routing problem with elementary shortest path based column generation. Comput. Oper. Res. 33, 2972–2990 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  17. Righini, G., Salani, M.: Symmetry helps: bounded bi-directional dynamic programming for the elementary shortest path problem with resource constraints. Discret. Optim. 3, 255–273 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  18. Kohl, N., Desrosiers, J., Madsen, O.B.G., Solomon, M.M., Soumis, F.: 2-path cuts for the vehicle routing problem with time windows. Transp. Sci. 33, 101–116 (1999)

    Article  MATH  Google Scholar 

  19. Prindezis, N., Kiranoudis, C.T., Marinos-Kouris, D.: A business-to-business fleet management service provider for central food market enterprises. J. Food Eng. 60, 203–210 (2003)

    Article  Google Scholar 

  20. Ioannoue, G., Kritikos, M.N., Prastacos, G.P.: A GIS-based decision support system for intra-city vehicle routing with time windows. J. Oper. Res. Soc. 53, 842–854 (2002)

    Article  Google Scholar 

  21. Fleischmann, B., Gietz, M., Gnutzmann, S.: Time-varying travel times in vehicle routing. Transp. Sci. 38, 160–173 (2004)

    Article  Google Scholar 

  22. Hiramatsu, A., Nose, K., Tenmoku, K., Morita, T.: Prediction of travel time in urban district based on state equation. Electron. Comm. Jpn. 92, 1–11 (2009)

    Article  Google Scholar 

  23. Ando, N., Taniguchi, E.: Travel time reliability in vehicle routing and scheduling with time windows. Networks Spatial Econ. 6, 293–311 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  24. Irnich, S., Villeneuve, D.: The shortest path problem with resource constraints and k-cycle elimination for k ≥ 3. Informs 18, 391–406 (2006)

    Article  MathSciNet  Google Scholar 

  25. Desrochers, M., Soumis, F.: A generalized permanent labeling algorithm for shortest path problem with time windows. Infor 26, 191–212 (1998)

    Google Scholar 

  26. Larsen, J.: Parallelization of the Vehicle Routing Problem with Time Windows. PhD. Thesis No. 62, Department of Mathematical Modeling (IMM) at the Technical University of Denmark (DTU) (1999)

  27. Qureshi, A.G., Taniguchi, E., Yamada, T.: An exact solution approach for vehicle routing and scheduling problems with soft time windows. Transport. Res. Part E 45, 960–977 (2009)

    Article  Google Scholar 

  28. Yamada, S.: The strategy and deployment plan for VICS. IEEE Comm. Mag. 34, 94–97 (1996)

    Google Scholar 

  29. Ministry of Land, Infrastructure and Transportation (MLIT) web site, http://www.mlit.go.jp/road/ITS/topindex/topindex_g03_3.html, accessed on date 15-04-2010

  30. ITS Handbook 2007–2008, Japan, Highway Industry Development Organization (HIDO), available online at, http://www.hido.or.jp/09kankou/HANDBOOK_all.pdf, accessed on date 16-01-2010

  31. Taniguchi, E., Thompson, R.G., Yamada, T., Duin, R.V.: City Logistics; Network Modeling and Intelligent Transport Systems. Pergamon, Oxford (2001)

    Google Scholar 

  32. National Institute of Land and Infrastructure Management (NILIM), Japan, Quantitative appraisal index calculations used for basic unit computation of CO2, NOx, SPM. 2003 (in Japanese)

  33. Yu, L., Qiao, F., Soltani, F.: Testing and Modeling Truck Emissions while Idling. research report 167650–1, Texas Southern University (2006)

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ali Gul Qureshi.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Qureshi, A.G., Taniguchi, E. & Yamada, T. An Analysis of Exact VRPTW Solutions on ITS Data-based Logistics Instances. Int. J. ITS Res. 10, 34–46 (2012). https://doi.org/10.1007/s13177-011-0040-2

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13177-011-0040-2

Keywords

Navigation