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The Tug Fleet Size Problem for Barge Line Operations: A Polynomial Algorithm

Author

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  • Ramchandran Jaikumar

    (Harvard University, Boston, Massachusetts)

  • Marius M. Solomon

    (Northeastern University, Boston, Massachusetts)

Abstract

In this paper the problem of minimizing the number of tugs required to transport a given number of barges between different ports in a river system is considered. The problem has traditionally been viewed as a vehicle routing problem and thus routing heuristics have been used. Advantage is taken of the feature that transfer time at ports is negligible, and the problem is modeled differently. A one-pass algorithm is developed which solves the problem in O ( n ) time. Extensions are made dealing with general river system structures and stochasticity in the demand pattern.

Suggested Citation

  • Ramchandran Jaikumar & Marius M. Solomon, 1987. "The Tug Fleet Size Problem for Barge Line Operations: A Polynomial Algorithm," Transportation Science, INFORMS, vol. 21(4), pages 264-272, November.
    • Handle: RePEc:inm:ortrsc:v:21:y:1987:i:4:p:264-272
    DOI: 10.1287/trsc.21.4.264
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    Cited by:

    1. Bakkehaug, Rikard & Eidem, Eirik Stamsø & Fagerholt, Kjetil & Hvattum, Lars Magnus, 2014. "A stochastic programming formulation for strategic fleet renewal in shipping," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 72(C), pages 60-76.
    2. Pantuso, Giovanni & Fagerholt, Kjetil & Hvattum, Lars Magnus, 2014. "A survey on maritime fleet size and mix problems," European Journal of Operational Research, Elsevier, vol. 235(2), pages 341-349.
    3. Wei, Xiaoyang & Jia, Shuai & Meng, Qiang & Tan, Kok Choon, 2020. "Tugboat scheduling for container ports," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    4. Vukadinovic, Katarina & Teodorovic, Dusan & Pavkovic, Goran, 1997. "A neural network approach to the vessel dispatching problem," European Journal of Operational Research, Elsevier, vol. 102(3), pages 473-487, November.

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