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Short-term liner ship fleet planning with container transshipment and uncertain container shipment demand

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  • Meng, Qiang
  • Wang, Tingsong
  • Wang, Shuaian
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    Abstract

    This paper proposes a short-term liner ship fleet planning problem by taking into account container transshipment and uncertain container shipment demand. Given a liner shipping service network comprising a number of ship routes, the problem is to determine the numbers and types of ships required in the fleet and assign each of these ships to a particular ship route to maximize the expected value of the total profit over a short-term planning horizon. These decisions have to be made prior to knowing the exact container shipment demand, which is affected by some unpredictable and uncontrollable factors. This paper thus formulates this realistic short-term planning problem as a two-stage stochastic integer programming model. A solution algorithm, integrating the sample average approximation with a dual decomposition and Lagrangian relaxation approach, is then proposed. Finally, a numerical example is used to evaluate the performance of the proposed model and solution algorithm.

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    File URL: http://www.sciencedirect.com/science/article/pii/S0377221712004808
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    Bibliographic Info

    Article provided by Elsevier in its journal European Journal of Operational Research.

    Volume (Year): 223 (2012)
    Issue (Month): 1 ()
    Pages: 96-105

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    Handle: RePEc:eee:ejores:v:223:y:2012:i:1:p:96-105

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    Web page: http://www.elsevier.com/locate/eor

    Related research

    Keywords: Logistics; Liner shipping; Container transshipment and uncertain demand; Stochastic integer programming; Sample average approximation with dual decomposition and Lagrangian relaxation;

    References

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    1. Song, Dong-Ping & Earl, Christopher F., 2008. "Optimal empty vehicle repositioning and fleet-sizing for two-depot service systems," European Journal of Operational Research, Elsevier, vol. 185(2), pages 760-777, March.
    2. Qiang Meng & Tingsong Wang, 2010. "A chance constrained programming model for short-term liner ship fleet planning problems," Maritime Policy & Management, Taylor & Francis Journals, vol. 37(4), pages 329-346, July.
    3. Karlaftis, Matthew G. & Kepaptsoglou, Konstantinos & Sambracos, Evangelos, 2009. "Containership routing with time deadlines and simultaneous deliveries and pick-ups," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 45(1), pages 210-221, January.
    4. Schütz, Peter & Tomasgard, Asgeir & Ahmed, Shabbir, 2009. "Supply chain design under uncertainty using sample average approximation and dual decomposition," European Journal of Operational Research, Elsevier, vol. 199(2), pages 409-419, December.
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    11. Gelareh, Shahin & Nickel, Stefan & Pisinger, David, 2010. "Liner shipping hub network design in a competitive environment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(6), pages 991-1004, November.
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    14. Gelareh, Shahin & Meng, Qiang, 2010. "A novel modeling approach for the fleet deployment problem within a short-term planning horizon," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(1), pages 76-89, January.
    15. Jos� Fernando �lvarez, 2009. "Joint Routing and Deployment of a Fleet of Container Vessels," Maritime Economics and Logistics, Palgrave Macmillan, vol. 11(2), pages 186-208, June.
    16. Sambracos, E. & Paravantis, J. A. & Tarantilis, C. D. & Kiranoudis, C. T., 2004. "Dispatching of small containers via coastal freight liners: The case of the Aegean Sea," European Journal of Operational Research, Elsevier, vol. 152(2), pages 365-381, January.
    17. Santoso, Tjendera & Ahmed, Shabbir & Goetschalckx, Marc & Shapiro, Alexander, 2005. "A stochastic programming approach for supply chain network design under uncertainty," European Journal of Operational Research, Elsevier, vol. 167(1), pages 96-115, November.
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    Citations

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    Cited by:
    1. Wang, Shuaian, 2014. "A novel hybrid-link-based container routing model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 61(C), pages 165-175.
    2. Wang, Shuaian & Meng, Qiang & Liu, Zhiyuan, 2013. "Containership scheduling with transit-time-sensitive container shipment demand," Transportation Research Part B: Methodological, Elsevier, vol. 54(C), pages 68-83.
    3. Hui, Yer Van & Gao, Jia & Leung, Lawrence & Wallace, Stein, 2014. "Airfreight forwarder’s shipment planning under uncertainty: A two-stage stochastic programming approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 66(C), pages 83-102.
    4. Liu, Zhiyuan & Meng, Qiang & Wang, Shuaian & Sun, Zhuo, 2014. "Global intermodal liner shipping network design," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 61(C), pages 28-39.
    5. SteadieSeifi, M. & Dellaert, N.P. & Nuijten, W. & Van Woensel, T. & Raoufi, R., 2014. "Multimodal freight transportation planning: A literature review," European Journal of Operational Research, Elsevier, vol. 233(1), pages 1-15.
    6. Pantuso, Giovanni & Fagerholt, Kjetil & Hvattum, Lars Magnus, 2014. "A survey on maritime fleet size and mix problems," European Journal of Operational Research, Elsevier, vol. 235(2), pages 341-349.

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