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Berth allocation with service priority

Author

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  • Imai, Akio
  • Nishimura, Etsuko
  • Papadimitriou, Stratos

Abstract

Over the past several years, port related charges in Japanese ports have been substantially higher than those charged in other major international hub ports. All major container ports in Japan feature so-called Dedicated Terminals in which cost-effectiveness is justified by huge container volume to be handled. One of the reasons cited for high port charges is a relative decrease in handling volume compared to the terminal capacity, resulting in inefficient use of the existing capacity. The use of the Multi-User Container Terminal (MUT) concept employed in some of the major container hub ports such as Hong Kong, Pusan, Hamburg and Rotterdam reduces redundant terminal space and results in substantial cost savings in cargo handling costs and therefore is desired for ports in Japan as well. One of the key issues in the MUT operation is the berth allocation to calling vessels. In a recent study, an allocation problem for the MUT was examined, in which each vessel was treated equally. However, as some vessel operators desire high priority services, the goal of this paper is to modify the existing formulation of the berth allocation problem in order to treat calling vessels at various service priorities by developing a genetic algorithm based heuristic for the resulting non-linear problem.

Suggested Citation

  • Imai, Akio & Nishimura, Etsuko & Papadimitriou, Stratos, 2003. "Berth allocation with service priority," Transportation Research Part B: Methodological, Elsevier, vol. 37(5), pages 437-457, June.
  • Handle: RePEc:eee:transb:v:37:y:2003:i:5:p:437-457
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    References listed on IDEAS

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    1. Ball, Michael O. & Kaku, Bharat K. & Vakhutinsky, Andrew, 1998. "Network-based formulations of the quadratic assignment problem," European Journal of Operational Research, Elsevier, vol. 104(1), pages 241-249, January.
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    4. Nishimura, Etsuko & Imai, Akio & Papadimitriou, Stratos, 2001. "Berth allocation planning in the public berth system by genetic algorithms," European Journal of Operational Research, Elsevier, vol. 131(2), pages 282-292, June.
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