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A non-linear traffic flow-based queuing model to estimate container terminal throughput with AGVs

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Listed:
  • Debjit Roy
  • Akash Gupta
  • René B.M. De Koster

Abstract

Efficient handling of containers at a terminal can reduce the overall vessel sojourn times and minimise operational costs. The internal transport of containers in these terminals is performed by vehicles that share a common guide path. The throughput capacity of a terminal may increase by increasing the number of vehicles; however, simultaneously congestion may reduce the effective vehicle speed. We model this situation accurately using a traffic flow-based closed queuing network model. The vehicle internal transport is modelled using a load-dependent server that captures the interaction between the number of vehicles in a transport segment and the effective vehicle speed. Using a non-linear traffic flow model, we show that the throughput reductions due to vehicle congestion can be as large as 85%. Hence, the effect of vehicle congestion during internal transport cannot be ignored. The model can also be used to determine the appropriate number of vehicles required to achieve the required terminal throughput by explicitly considering the effect of vehicle congestion.

Suggested Citation

  • Debjit Roy & Akash Gupta & René B.M. De Koster, 2016. "A non-linear traffic flow-based queuing model to estimate container terminal throughput with AGVs," International Journal of Production Research, Taylor & Francis Journals, vol. 54(2), pages 472-493, January.
    • Handle: RePEc:taf:tprsxx:v:54:y:2016:i:2:p:472-493
    DOI: 10.1080/00207543.2015.1056321
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    References listed on IDEAS

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    1. Roy, D. & de Koster, M.B.M., 2014. "Modeling and Design of Container Terminal Operations," ERIM Report Series Research in Management ERS-2014-008-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    2. Meersmans, P.J.M. & Dekker, R., 2001. "Operations research supports container handling," Econometric Institute Research Papers EI 2001-22, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
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    Cited by:

    1. Amir Gharehgozli & Debjit Roy & Suruchika Saini & Jan-Kees Ommeren, 2023. "Loading and unloading trains at the landside of container terminals," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 25(3), pages 549-575, September.
    2. Feng, Xuehao & He, Yucheng & Kim, Kap-Hwan, 2022. "Space planning considering congestion in container terminal yards," Transportation Research Part B: Methodological, Elsevier, vol. 158(C), pages 52-77.
    3. Zhang, Xiaoju & Zeng, Qingcheng & Sheu, Jiuh-Biing, 2019. "Modeling the productivity and stability of a terminal operation system with quay crane double cycling," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 181-197.
    4. Zhen, Lu, 2016. "Modeling of yard congestion and optimization of yard template in container ports," Transportation Research Part B: Methodological, Elsevier, vol. 90(C), pages 83-104.
    5. Roy, Debjit & van Ommeren, Jan-Kees & de Koster, René & Gharehgozli, Amir, 2022. "Modeling landside container terminal queues: Exact analysis and approximations," Transportation Research Part B: Methodological, Elsevier, vol. 162(C), pages 73-102.
    6. Fragapane, Giuseppe & de Koster, René & Sgarbossa, Fabio & Strandhagen, Jan Ola, 2021. "Planning and control of autonomous mobile robots for intralogistics: Literature review and research agenda," European Journal of Operational Research, Elsevier, vol. 294(2), pages 405-426.
    7. Amir Gharehgozli & Nima Zaerpour & Rene Koster, 2020. "Container terminal layout design: transition and future," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 22(4), pages 610-639, December.
    8. Roy, Debjit & de Koster, René, 2018. "Stochastic modeling of unloading and loading operations at a container terminal using automated lifting vehicles," European Journal of Operational Research, Elsevier, vol. 266(3), pages 895-910.

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