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An empirical model for estimating berth and sailing times of mega container ships

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  • Mohamed Grida
  • Chung-Yee Lee

Abstract

We provide two empirical models for calculating the sailing time and berth time of maritime container liner networks to effectively model the ambiguity associated with sea and port contingency for ex-ante decisions of fleet deployment and route planning. The models are based on recorded AIS data of 110 mega vessels including all the operating container mega vessels with a capacity of 16,000 TEU or more during the summer of 2015. The models are able to estimate the sailing time (with R2 of 0.974) and the berth time (with R2 of 0.895) without knowledge of any operational-level explanatory variables. The models are validated against the published East Asia–North Europe services. Moreover, the study reveals that vessel operators adopt different berthing and sailing strategies even under the same conditions.

Suggested Citation

  • Mohamed Grida & Chung-Yee Lee, 2018. "An empirical model for estimating berth and sailing times of mega container ships," Maritime Policy & Management, Taylor & Francis Journals, vol. 45(8), pages 1078-1093, November.
    • Handle: RePEc:taf:marpmg:v:45:y:2018:i:8:p:1078-1093
    DOI: 10.1080/03088839.2018.1452304
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    Cited by:

    1. Milan Janić, 2018. "Multidimensional examination of the performances of a liner shipping network: trunk line/route operated by conventional (Panamax Max) and mega (ULC - ultra large container) ships," Journal of Shipping and Trade, Springer, vol. 3(1), pages 1-35, December.
    2. Lorenz Kolley & Nicolas Rückert & Marvin Kastner & Carlos Jahn & Kathrin Fischer, 2023. "Robust berth scheduling using machine learning for vessel arrival time prediction," Flexible Services and Manufacturing Journal, Springer, vol. 35(1), pages 29-69, March.
    3. Zhang, Ruiyou & Huang, Chao & Feng, Xuehao, 2020. "Empty container repositioning with foldable containers in a river transport network considering the limitations of bridge heights," Transportation Research Part A: Policy and Practice, Elsevier, vol. 133(C), pages 197-213.

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