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A novel modeling approach for the fleet deployment problem within a short-term planning horizon

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  • Gelareh, Shahin
  • Meng, Qiang
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    Abstract

    This paper is concerned with model development for a short-term fleet deployment problem of liner shipping operations. We first present a mixed integer nonlinear programming model in which the optimal vessel speeds for different vessel types on different routes are interpreted as their realistic optimal travel times. We then linearize the proposed nonlinear model and obtain a mixed integer linear programming (MILP) model that can be efficiently solved by a standard mixed integer programming solver such as CPLEX. The MILP model determines the optimal route service frequency pattern and take into account the time window constraints of shipping services. Finally, we report our numerical results and performance of CPLEX on randomly generated instances.

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    File URL: http://www.sciencedirect.com/science/article/pii/S1366554509000829
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    Bibliographic Info

    Article provided by Elsevier in its journal Transportation Research Part E: Logistics and Transportation Review.

    Volume (Year): 46 (2010)
    Issue (Month): 1 (January)
    Pages: 76-89

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    Handle: RePEc:eee:transe:v:46:y:2010:i:1:p:76-89

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    Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/600244/description#description

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    Related research

    Keywords: Liner shipping Containership Fleet deployment Mixed integer programming Linearization;

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    Citations

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    Cited by:
    1. Meng, Qiang & Wang, Tingsong & Wang, Shuaian, 2012. "Short-term liner ship fleet planning with container transshipment and uncertain container shipment demand," European Journal of Operational Research, Elsevier, vol. 223(1), pages 96-105.
    2. Wang, Shuaian & Meng, Qiang, 2012. "Liner ship fleet deployment with container transshipment operations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(2), pages 470-484.
    3. Gelareh, Shahin & Pisinger, David, 2011. "Fleet deployment, network design and hub location of liner shipping companies," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(6), pages 947-964.
    4. Wang, Shuaian & Meng, Qiang, 2012. "Sailing speed optimization for container ships in a liner shipping network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(3), pages 701-714.
    5. Wang, Tingsong & Meng, Qiang & Wang, Shuaian & Tan, Zhijia, 2013. "Risk management in liner ship fleet deployment: A joint chance constrained programming model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 60(C), pages 1-12.
    6. Meng, Qiang & Wang, Shuaian, 2012. "Liner ship fleet deployment with week-dependent container shipment demand," European Journal of Operational Research, Elsevier, vol. 222(2), pages 241-252.
    7. Wang, Shuaian & Meng, Qiang, 2012. "Liner ship route schedule design with sea contingency time and port time uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 46(5), pages 615-633.
    8. 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.
    9. Wang, Shuaian & Meng, Qiang & Liu, Zhiyuan, 2013. "Bunker consumption optimization methods in shipping: A critical review and extensions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 53(C), pages 49-62.
    10. 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.
    11. Christiansen, Marielle & Fagerholt, Kjetil & Nygreen, Bjørn & Ronen, David, 2013. "Ship routing and scheduling in the new millennium," European Journal of Operational Research, Elsevier, vol. 228(3), pages 467-483.

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