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A Branch-and-Price-and-Cut Method for Ship Scheduling with Limited Risk

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  • Hee-Su Hwang

    (US Airways, Tempe, Arizona 85281)

  • Siriwat Visoldilokpun

    (Department of Industrial and Manufacturing Systems Engineering, University of Texas at Arlington, Arlington, Texas 76019)

  • Jay M. Rosenberger

    (Department of Industrial and Manufacturing Systems Engineering, University of Texas at Arlington, Arlington, Texas 76019)

Abstract

Maritime logistics operations are full of uncertainty such as severe weather, mechanical problems, strikes, and fluctuating freight rates. Traditional ship-scheduling models ignore uncertainty, even in highly volatile markets. Although ship operators can increase revenue by delivering many spot cargoes, they have to embrace the risk of the fluctuation of spot rates. We present a set-packing model that limits risk using a quadratic variance constraint. We use a traditional Kelley's cutting plane algorithm and a delayed column-and-cut generation (branch-and-price-and-cut) algorithm on medium-sized ship-scheduling problems with restricted variance. We develop a second set of cuts that are more restrictive under certain conditions. Computational results show that the variance of profit can be significantly reduced with a reasonable increase in cost.

Suggested Citation

  • Hee-Su Hwang & Siriwat Visoldilokpun & Jay M. Rosenberger, 2008. "A Branch-and-Price-and-Cut Method for Ship Scheduling with Limited Risk," Transportation Science, INFORMS, vol. 42(3), pages 336-351, August.
  • Handle: RePEc:inm:ortrsc:v:42:y:2008:i:3:p:336-351
    DOI: 10.1287/trsc.1070.0218
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    References listed on IDEAS

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    Cited by:

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    2. Asteris, Michael & Collins, Alan & Jones, Dylan F., 2012. "Container port infrastructure in north-west Europe: Policy-level modeling," Journal of Policy Modeling, Elsevier, vol. 34(2), pages 312-324.
    3. Wu, Lingxiao & Wang, Shuaian & Laporte, Gilbert, 2021. "The Robust Bulk Ship Routing Problem with Batched Cargo Selection," Transportation Research Part B: Methodological, Elsevier, vol. 143(C), pages 124-159.
    4. Ksciuk, Jana & Kuhlemann, Stefan & Tierney, Kevin & Koberstein, Achim, 2023. "Uncertainty in maritime ship routing and scheduling: A Literature review," European Journal of Operational Research, Elsevier, vol. 308(2), pages 499-524.
    5. Zhixing Luo & Hu Qin & T. C. E. Cheng & Qinghua Wu & Andrew Lim, 2021. "A Branch-and-Price-and-Cut Algorithm for the Cable-Routing Problem in Solar Power Plants," INFORMS Journal on Computing, INFORMS, vol. 33(2), pages 452-476, May.
    6. 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.
    7. Harilaos N. Psaraftis, 2019. "Ship routing and scheduling: the cart before the horse conjecture," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 21(1), pages 111-124, March.
    8. Zhijia Tan & Yadong Wang & Qiang Meng & Zhixue Liu, 2018. "Joint Ship Schedule Design and Sailing Speed Optimization for a Single Inland Shipping Service with Uncertain Dam Transit Time," Service Science, INFORMS, vol. 52(6), pages 1570-1588, December.
    9. Pang, King-Wah & Xu, Zhou & Li, Chung-Lun, 2011. "Ship routing problem with berthing time clash avoidance constraints," International Journal of Production Economics, Elsevier, vol. 131(2), pages 752-762, June.

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