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Ballast water dynamic allocation optimization model and analysis for safe and reliable operation of floating cranes

Author

Listed:
  • Zhijie Liu

    (Dalian Maritime University)

  • Jianyu Jiang

    (Dalian Maritime University)

  • Zhiqiang Gan

    (Tianjin Pumps & Machinery Group Co.)

  • Chengxin Lin

    (Dalian Maritime University)

Abstract

Ballast water can adjust the heel and trim and its optimal allocation is very important for assuring safe operation of floating cranes. The combined ballast system based on pumps and water gravity self-flow can transfer a large amount of ballast water in a short time and is widely used for large floating cranes. Based on the hydrostatics of ships and optimal theories, the optimization model of ballast water allocation is built to minimize the ballasting time of floating cranes using the combined ballast system. In this model, the variations of water levels for all ballast tanks are taken as the optimization variables and the hull balance in the ballasting process as the constraint conditions. The ballasting process can be considered as the Markov process, so the dynamic programming solving model is established for the dynamic ballasting. The analysis of a numerical simulation case shows that the ballasting time of the combined ballast system obviously reduces compared with the ballast pump system. The tilted angles of the floating cranes are very small which assures the operation safety and reliability of floating cranes. The established optimization model and method can obtain the optimal ballasting process, effectively reduce the ballasting time, and provide decision model and solving algorithm support for improving the efficiency, and achieving the dynamic ballasting automatic or intelligent control of floating cranes based on computers.

Suggested Citation

  • Zhijie Liu & Jianyu Jiang & Zhiqiang Gan & Chengxin Lin, 2022. "Ballast water dynamic allocation optimization model and analysis for safe and reliable operation of floating cranes," Annals of Operations Research, Springer, vol. 311(1), pages 279-294, April.
    • Handle: RePEc:spr:annopr:v:311:y:2022:i:1:d:10.1007_s10479-019-03213-2
    DOI: 10.1007/s10479-019-03213-2
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    References listed on IDEAS

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    1. Ulrike Ritzinger & Jakob Puchinger & Richard Hartl, 2016. "Dynamic programming based metaheuristics for the dial-a-ride problem," Annals of Operations Research, Springer, vol. 236(2), pages 341-358, January.
    2. Mi, Jinhua & Li, Yan-Feng & Peng, Weiwen & Huang, Hong-Zhong, 2018. "Reliability analysis of complex multi-state system with common cause failure based on evidential networks," Reliability Engineering and System Safety, Elsevier, vol. 174(C), pages 71-81.
    3. Ulrike Ritzinger & Jakob Puchinger & Richard F. Hartl, 2016. "Dynamic programming based metaheuristics for the dial-a-ride problem," Annals of Operations Research, Springer, vol. 236(2), pages 341-358, January.
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