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A Stackelberg-game approach to support the design of logistic terminals

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  • Catalano, Mario
  • Migliore, Marco

Abstract

This paper deals with the design of logistic terminals taking Sicily, in the South of Italy, as a case study. It focuses on consolidation terminals for truckers and addresses the problem of optimising location pattern and public share in investments. This problem is solved through a Stackelberg game between the designer and the collective of road carriers. So a bilevel approach combines a system-optimum problem, at the upper level, with the carrier equilibrium problem, at the lower level. The choice behaviour of the lower-level player is simulated by a random utility model. The output of the game suggests that private companies and society should share the investments and the public contribution should be high; furthermore, transhipment and consolidation services should be concentrated at few terminals to exploit fully economies of scale at the expense of the average travel time to reach the logistic platforms.

Suggested Citation

  • Catalano, Mario & Migliore, Marco, 2014. "A Stackelberg-game approach to support the design of logistic terminals," Journal of Transport Geography, Elsevier, vol. 41(C), pages 63-73.
    • Handle: RePEc:eee:jotrge:v:41:y:2014:i:c:p:63-73
    DOI: 10.1016/j.jtrangeo.2014.08.010
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    References listed on IDEAS

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    1. Bergantino, Angela S. & Bierlaire, Michel & Catalano, Mario & Migliore, Marco & Amoroso, Salvatore, 2013. "Taste heterogeneity and latent preferences in the choice behaviour of freight transport operators," Transport Policy, Elsevier, vol. 30(C), pages 77-91.
    2. Klose, Andreas & Drexl, Andreas, 2005. "Facility location models for distribution system design," European Journal of Operational Research, Elsevier, vol. 162(1), pages 4-29, April.
    3. Portugal, Licinio da Silva & Morgado, Andréa Vaz & Júnior, Orlando Lima, 2011. "Location of cargo terminals in metropolitan areas of developing countries: the Brazilian case," Journal of Transport Geography, Elsevier, vol. 19(4), pages 900-910.
    4. Taniguchi, Eiichi & Noritake, Michihiko & Yamada, Tadashi & Izumitani, Toru, 1999. "Optimal size and location planning of public logistics terminals," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 35(3), pages 207-222, September.
    5. Erdemir, Elif Tokar & Batta, Rajan & Spielman, Seth & Rogerson, Peter A. & Blatt, Alan & Flanigan, Marie, 2008. "Location coverage models with demand originating from nodes and paths: Application to cellular network design," European Journal of Operational Research, Elsevier, vol. 190(3), pages 610-632, November.
    6. Arunotayanun, Kriangkrai & Polak, John W., 2011. "Taste heterogeneity and market segmentation in freight shippers' mode choice behaviour," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(2), pages 138-148, March.
    7. Louviere,Jordan J. & Hensher,David A. & Swait,Joffre D., 2000. "Stated Choice Methods," Cambridge Books, Cambridge University Press, number 9780521788304, September.
    8. Carlos F. Daganzo, 1987. "The Break-Bulk Role of Terminals in Many-to-Many Logistic Networks," Operations Research, INFORMS, vol. 35(4), pages 543-555, August.
    9. Yaron Hollander & Joseph Prashker, 2006. "The applicability of non-cooperative game theory in transport analysis," Transportation, Springer, vol. 33(5), pages 481-496, September.
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    Cited by:

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    2. Shuangyan Li & Yijing Liang & Zhenjie Wang & Dezhi Zhang, 2021. "An Optimization Model of a Sustainable City Logistics Network Design Based on Goal Programming," Sustainability, MDPI, vol. 13(13), pages 1-20, July.

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