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Optimal operations of transportation fleet for unloading activities at container ports

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  • Kang, Seungmo
  • Medina, Juan C.
  • Ouyang, Yanfeng

Abstract

This paper presents mathematical models that optimize the size of transportation fleet (cranes and trucks) for unloading operations at container terminals. A cyclic queue model is used to study the steady-state port throughput, which then yields the optimum fleet size for long-term operations. This model allows for stochastic operations such as exponentially distributed crane service times. In order to allow for generally distributed crane service times and truck travel times, an approach based on Markovian decision process is also proposed. This model provides dynamic operational policies for fleet management. Both models are implemented and examined with empirical data from the Port of Balboa, Panama. These models are also extended to unloading operations that involve multiple berths.

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  • Kang, Seungmo & Medina, Juan C. & Ouyang, Yanfeng, 2008. "Optimal operations of transportation fleet for unloading activities at container ports," Transportation Research Part B: Methodological, Elsevier, vol. 42(10), pages 970-984, December.
    • Handle: RePEc:eee:transb:v:42:y:2008:i:10:p:970-984
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    Cited by:

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    3. Carlo, Héctor J. & Vis, Iris F.A. & Roodbergen, Kees Jan, 2014. "Transport operations in container terminals: Literature overview, trends, research directions and classification scheme," European Journal of Operational Research, Elsevier, vol. 236(1), pages 1-13.
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    5. 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.
    6. Alessia Donato & David Carfì & Beatrice Blandina, 2018. "Coopetitive Games for Management of Marine Transportation Activity: A Study Case," Mathematics, MDPI, vol. 6(12), pages 1-17, December.
    7. 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.
    8. 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.
    9. Yang, Xuejing & Low, Joyce M.W. & Tang, Loon Ching, 2011. "Analysis of intermodal freight from China to Indian Ocean: A goal programming approach," Journal of Transport Geography, Elsevier, vol. 19(4), pages 515-527.
    10. Zehendner, Elisabeth & Feillet, Dominique, 2014. "Benefits of a truck appointment system on the service quality of inland transport modes at a multimodal container terminal," European Journal of Operational Research, Elsevier, vol. 235(2), pages 461-469.
    11. Xiaoju Zhang & Huijuan Li & Meng Wu, 2022. "Optimization of Resource Allocation in Automated Container Terminals," Sustainability, MDPI, vol. 14(24), pages 1-16, December.
    12. Leachman, Robert C. & Jula, Payman, 2011. "Congestion analysis of waterborne, containerized imports from Asia to the United States," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(6), pages 992-1004.
    13. Amir Hossein Gharehgozli & Gilbert Laporte & Yugang Yu & René de Koster, 2015. "Scheduling Twin Yard Cranes in a Container Block," Transportation Science, INFORMS, vol. 49(3), pages 686-705, August.
    14. Ahmed Karam & Amr Eltawil & Kristian Hegner Reinau, 2020. "Energy-Efficient and Integrated Allocation of Berths, Quay Cranes, and Internal Trucks in Container Terminals," Sustainability, MDPI, vol. 12(8), pages 1-24, April.
    15. Wang, Shuaian & Meng, Qiang & Liu, Zhiyuan, 2013. "Containership scheduling with transit-time-sensitive container shipment demand," Transportation Research Part B: Methodological, Elsevier, vol. 54(C), pages 68-83.
    16. Yunting Song & Nuo Wang, 2021. "On probability distributions of the time deviation law of container liner ships under interference uncertainty," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(1), pages 354-367, January.
    17. Gharehgozli, A.H. & Roy, D. & de Koster, M.B.M., 2014. "Sea Container Terminals," ERIM Report Series Research in Management ERS-2014-009-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.

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