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Port space allocation with a time dimension

Author

Listed:
  • Z Fu

    (Princeton University)

  • Y Li

    (Hong Kong University of Science and Technology)

  • A Lim

    (Hong Kong University of Science and Technology)

  • B Rodrigues

    (Singapore Management University)

Abstract

In the Port of Singapore, as in many other ports, space has to be allocated in yards for inbound and transit cargo. Requests for container space occur at different times during the planning period, and are made for different quantities and sizes of containers. In this paper, we study space allocation under these conditions. We reduce the problem to a two-dimensional packing problem with a time dimension. Since the problem is NP-hard, we develop heuristic algorithms, using tabu search, simulated annealing, a genetic algorithm and ‘squeaky wheel’ optimization, as solution approaches. Extensive computational experiments compare the algorithms, which are shown to be effective for the problem.

Suggested Citation

  • Z Fu & Y Li & A Lim & B Rodrigues, 2007. "Port space allocation with a time dimension," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(6), pages 797-807, June.
    • Handle: RePEc:pal:jorsoc:v:58:y:2007:i:6:d:10.1057_palgrave.jors.2602192
    DOI: 10.1057/palgrave.jors.2602192
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    References listed on IDEAS

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    1. Federico Sabria & Carlos F. Daganzo, 1989. "Approximate Expressions for Queueing Systems with Scheduled Arrivals and Established Service Order," Transportation Science, INFORMS, vol. 23(3), pages 159-165, August.
    2. Bruce Hajek, 1988. "Cooling Schedules for Optimal Annealing," Mathematics of Operations Research, INFORMS, vol. 13(2), pages 311-329, May.
    3. Hopper, E. & Turton, B. C. H., 2001. "An empirical investigation of meta-heuristic and heuristic algorithms for a 2D packing problem," European Journal of Operational Research, Elsevier, vol. 128(1), pages 34-57, January.
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    Citations

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    Cited by:

    1. Carlo, Héctor J. & Vis, Iris F.A. & Roodbergen, Kees Jan, 2014. "Storage yard operations in container terminals: Literature overview, trends, and research directions," European Journal of Operational Research, Elsevier, vol. 235(2), pages 412-430.
    2. Matthew E. H. Petering & Yong Wu & Wenkai Li & Mark Goh & Robert Souza & Katta G. Murty, 2017. "Real-time container storage location assignment at a seaport container transshipment terminal: dispersion levels, yard templates, and sensitivity analyses," Flexible Services and Manufacturing Journal, Springer, vol. 29(3), pages 369-402, December.
    3. Umang, Nitish & Bierlaire, Michel & Vacca, Ilaria, 2013. "Exact and heuristic methods to solve the berth allocation problem in bulk ports," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 54(C), pages 14-31.

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