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Timber terminal capacity planning through queuing theory

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  • Susila Munisamy

    (Department of Applied Statistics, University of Malaya, Kuala Lumpur 50603, Malaysia)

Abstract

This article develops a port planning and operations model for capacity planning at a timber terminal. The analytical model underlying the system is the closed queuing network model. The model evaluates the efficiency of the timber terminal in relation to the cargo handling system and its impact on terminal throughput capacity. The model considers the interaction between cargo handling elements of a timber terminal, that is forklifts, tractors, trailers and quay cranes, to investigate congestion points and how each element affects the other parts of the cargo handling system. The output of the model is the performance statistics of the cargo handling equipments of the terminal, the throughput of quay cranes and the forecast of the terminal's throughput capacity. The implementation of the model to Port Klang timber terminal shows how it can provide guidance for port authorities and port operators in formulating economically efficient operational and expansion strategies.

Suggested Citation

  • Susila Munisamy, 2010. "Timber terminal capacity planning through queuing theory," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 12(2), pages 147-161, June.
    • Handle: RePEc:pal:marecl:v:12:y:2010:i:2:p:147-161
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    Citations

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    Cited by:

    1. Neagoe, Mihai & Taskhiri, Mohammad Sadegh & Nguyen, Hong-Oanh & Hvolby, Hans-Henrik & Turner, Paul A., 2018. "Exploring congestion impact beyond the bulk cargo terminal gate," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Jahn, Carlos & Kersten, Wolfgang & Ringle, Christian M. (ed.), Logistics 4.0 and Sustainable Supply Chain Management: Innovative Solutions for Logistics and Sustainable Supply Chain Management in the Context of In, volume 26, pages 61-80, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    2. Daisik Nam & Minyoung Park, 2020. "Improving the Operational Efficiency of Parcel Delivery Network with a Bi-Level Decision Making Model," Sustainability, MDPI, vol. 12(19), pages 1-19, September.
    3. Naima Saeed & Dong-Wook Song & Otto Andersen, 2018. "Governance mode for port congestion mitigation: A transaction cost perspective," Netnomics, Springer, vol. 19(3), pages 159-178, December.
    4. Branislav Dragovic & Nenad Dj. Zrnic, 2011. "A Queuing Model Study of Port Performance Evolution," Analele Universitatii "Eftimie Murgu" Resita Fascicola de Inginerie, "Eftimie Murgu" University of Resita, vol. 2(XVIII), pages 65-76, December.
    5. Batabyal, Amitrajeet A. & DeAngelo, Gregory J., 2012. "Goods allocation by queuing and the occurrence of violence: A probabilistic analysis," International Review of Economics & Finance, Elsevier, vol. 24(C), pages 1-7.

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