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Essential elements in tactical planning models for container liner shipping

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  • Wang, Shuaian

Abstract

Tactical planning models for liner shipping problems such as network design and fleet deployment usually minimize the total cost or maximize the total profit subject to constraints including ship availability, service frequency, ship capacity, and transshipment. Most models in the literature do not consider slot-purchasing, multi-type containers, empty container repositioning, or ship repositioning, and they formulate the numbers of containers to transport as continuous variables. This paper develops a mixed-integer linear programming model that captures all these elements. It further examines from the theoretical point of view the additional computational burden introduced by incorporating these elements in the planning model. Extensive numerical experiments are conducted to evaluate the effects of the elements on tactical planning decisions. Results demonstrate that slot-purchasing and empty container repositioning have the largest impact on tactical planning decisions and relaxing the numbers of containers as continuous variables has little impact on the decisions.

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  • Wang, Shuaian, 2013. "Essential elements in tactical planning models for container liner shipping," Transportation Research Part B: Methodological, Elsevier, vol. 54(C), pages 84-99.
    • Handle: RePEc:eee:transb:v:54:y:2013:i:c:p:84-99
    DOI: 10.1016/j.trb.2013.04.001
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    17. 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.
    18. Song, Dong-Ping & Dong, Jing-Xin, 2012. "Cargo routing and empty container repositioning in multiple shipping service routes," Transportation Research Part B: Methodological, Elsevier, vol. 46(10), pages 1556-1575.
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    Cited by:

    1. Nguyen Khoi Tran & Hans-Dietrich Haasis & Tobias Buer, 2017. "Container shipping route design incorporating the costs of shipping, inland/feeder transport, inventory and CO2 emission," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 19(4), pages 667-694, December.
    2. Bell, Michael G.H. & Pan, Jing-Jing & Teye, Collins & Cheung, Kam-Fung & Perera, Supun, 2020. "An entropy maximizing approach to the ferry network design problem," Transportation Research Part B: Methodological, Elsevier, vol. 132(C), pages 15-28.
    3. Meng, Qiang & Lee, Chung-Yee, 2016. "Liner container assignment model with transit-time-sensitive container shipment demand and its applicationsAuthor-Name: Wang, Shuaian," Transportation Research Part B: Methodological, Elsevier, vol. 90(C), pages 135-155.
    4. Herrera Rodriguez, Manuel & Agrell, Per J. & Manrique-de-Lara-Peñate, Casiano & Trujillo, Lourdes, 2022. "A multi-criteria fleet deployment model for cost, time and environmental impact," International Journal of Production Economics, Elsevier, vol. 243(C).
    5. 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.
    6. Najafi, Mehdi & Zolfagharinia, Hossein, 2021. "Pricing and quality setting strategy in maritime transportation: Considering empty repositioning and demand uncertainty," International Journal of Production Economics, Elsevier, vol. 240(C).
    7. Wang, Shuaian & Liu, Zhiyuan & Meng, Qiang, 2015. "Segment-based alteration for container liner shipping network design," Transportation Research Part B: Methodological, Elsevier, vol. 72(C), pages 128-145.
    8. Lai, Xiaofan & Wu, Lingxiao & Wang, Kai & Wang, Fan, 2022. "Robust ship fleet deployment with shipping revenue management," Transportation Research Part B: Methodological, Elsevier, vol. 161(C), pages 169-196.
    9. Chen Li & Xiangtong Qi & Chung-Yee Lee, 2015. "Disruption Recovery for a Vessel in Liner Shipping," Transportation Science, INFORMS, vol. 49(4), pages 900-921, November.
    10. Ng, ManWo & Lo, Hong K., 2016. "Robust models for transportation service network design," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 378-386.
    11. Ming Liu & Rongfan Liu & E Zhang & Chengbin Chu, 2022. "Eco-friendly container transshipment route scheduling problem with repacking operations," Journal of Combinatorial Optimization, Springer, vol. 43(5), pages 1010-1035, July.
    12. Wang, Shuaian, 2015. "Optimal sequence of container ships in a string," European Journal of Operational Research, Elsevier, vol. 246(3), pages 850-857.
    13. An, Kun & Lo, Hong K., 2014. "Ferry service network design with stochastic demand under user equilibrium flows," Transportation Research Part B: Methodological, Elsevier, vol. 66(C), pages 70-89.
    14. Alaa Abdelshafie & May Salah & Tomaž Kramberger & Dejan Dragan, 2022. "Repositioning and Optimal Re-Allocation of Empty Containers: A Review of Methods, Models, and Applications," Sustainability, MDPI, vol. 14(11), pages 1-23, May.
    15. Ming Liu & Rongfan Liu & E Zhang & Chengbin Chu, 0. "Eco-friendly container transshipment route scheduling problem with repacking operations," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-26.
    16. Tobias Buer & Rasmus Haass, 2018. "Cooperative liner shipping network design by means of a combinatorial auction," Flexible Services and Manufacturing Journal, Springer, vol. 30(4), pages 686-711, December.
    17. Wetzel, Daniel & Tierney, Kevin, 2020. "Integrating fleet deployment into liner shipping vessel repositioning," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 143(C).
    18. Wong, Eugene Y.C. & Tai, Allen H. & Raman, Mardjuki, 2015. "A maritime container repositioning yield-based optimization model with uncertain upsurge demand," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 82(C), pages 147-161.

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