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Liner ship route capacity utilization estimation with a bounded polyhedral container shipment demand pattern

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  • Wang, Shuaian
  • Meng, Qiang
  • Bell, Michael G.H.

Abstract

This paper aims to estimate capacity utilization of a liner ship route with a bounded polyhedral container shipment demand pattern, arising in the liner container shipping industry. The proposed maximum and minimum liner ship route capacity utilization problems are formulated as a linear programming model and a min–max model, respectively. We examine two fundamental properties of the min–max model. These two nice properties enable us to develop two ε-optimal global optimization algorithms for solving the min–max model, which find a globally ε-optimal solution by iteratively cutting off the bounded polyhedral container shipment demand set with a cut. The latter algorithm overcomes non-convexity of the remaining feasible demand set generated by the former algorithm via a novel hyperplane cut. Each hyperplane cut can assure that the current vertex of the polyhedral demand set is cut off, whereas solutions that may improve the current one by more than a factor of ε are retained. Extensive numerical experiments for problems larger than those encountered in real applications demonstrate the computational efficacy of the latter algorithm.

Suggested Citation

  • Wang, Shuaian & Meng, Qiang & Bell, Michael G.H., 2013. "Liner ship route capacity utilization estimation with a bounded polyhedral container shipment demand pattern," Transportation Research Part B: Methodological, Elsevier, vol. 47(C), pages 57-76.
  • Handle: RePEc:eee:transb:v:47:y:2013:i:c:p:57-76
    DOI: 10.1016/j.trb.2012.07.011
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    Cited by:

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    4. Qinghe Sun & Li Chen & Mabel C. Chou & Qiang Meng, 2023. "Mitigating the financial risk behind emission cap compliance: A case in maritime transportation," Production and Operations Management, Production and Operations Management Society, vol. 32(1), pages 283-300, January.
    5. Feng-Ming Tsai & Linda J.W. Huang, 2017. "Using artificial neural networks to predict container flows between the major ports of Asia," International Journal of Production Research, Taylor & Francis Journals, vol. 55(17), pages 5001-5010, September.
    6. Xing, Hui & Spence, Stephen & Chen, Hua, 2020. "A comprehensive review on countermeasures for CO2 emissions from ships," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    7. Ng, ManWo, 2014. "Distribution-free vessel deployment for liner shipping," European Journal of Operational Research, Elsevier, vol. 238(3), pages 858-862.
    8. Manuel Herrera & Per J. Agrell & Casiano Manrique-de-Lara-Peñate & Lourdes Trujillo, 2017. "Vessel capacity restrictions in the fleet deployment problem: an application to the Panama Canal," Annals of Operations Research, Springer, vol. 253(2), pages 845-869, June.
    9. 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.
    10. Dong, Jing-Xin & Lee, Chung-Yee & Song, Dong-Ping, 2015. "Joint service capacity planning and dynamic container routing in shipping network with uncertain demands," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 404-421.
    11. Wang, Shuaian, 2015. "Optimal sequence of container ships in a string," European Journal of Operational Research, Elsevier, vol. 246(3), pages 850-857.
    12. Qiang Meng & Shuaian Wang & Henrik Andersson & Kristian Thun, 2014. "Containership Routing and Scheduling in Liner Shipping: Overview and Future Research Directions," Transportation Science, INFORMS, vol. 48(2), pages 265-280, May.
    13. Chen, Kang & Chen, Dongxu & Sun, Xueshan & Yang, Zhongzhen, 2016. "Container Ocean-transportation System Design with the factors of demand fluctuation and choice inertia of shippers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 95(C), pages 267-281.
    14. 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.

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