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A mathematical model to evaluate different train loading and stacking policies in a container terminal

Author

Listed:
  • Daniela Ambrosino

    (Department of Economics and Business Studies, University of Genoa, Genoa, Italy)

  • Claudia Caballini

    (Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa,Genoa, Italy)

  • Silvia Siri

    (Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa,Genoa, Italy)

Abstract

A container terminal is devoted to transfer containers from sea to land and vice versa in the most efficient way. The main objective of a container terminal is to optimize, in terms of times and costs, the activities related to container handling and forwarding. As regards the hinterland side, a crucial activity is represented by train loading/unloading, considering also the increasing importance assumed by rail transportation in allowing the move of large volumes of goods in/out of the logistic transportation nodes. This article pursues the modelling and comparison of different train loading policies by varying the storage area strategies in order to evaluate them and determine the most effective policy for ensuring quickness and efficiency in the terminal. With respect to the train loading policies, all the possible configurations are taken into account, starting from a pure sequential loading by the rail overhead travelling crane, which consequently implies some rehandling operations in the yard, up to the opposite situation in which non-sequential loading operations are allowed in order to avoid rehandling activities. These loading policies are analysed by varying the stacking strategies adopted in the yard where containers can be stored taking into consideration different factors (commercial priorities, weights, and so on). By using real data in relation to the physical characteristics of containers, trains and wagons, a proper experimental campaign has been performed in order to test the effectiveness of the different scenarios described above.

Suggested Citation

  • Daniela Ambrosino & Claudia Caballini & Silvia Siri, 2013. "A mathematical model to evaluate different train loading and stacking policies in a container terminal," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 15(3), pages 292-308, September.
    • Handle: RePEc:pal:marecl:v:15:y:2013:i:3:p:292-308
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    Citations

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    Cited by:

    1. Zhongbin Zhao & Xifu Wang & Suxin Cheng & Wei Liu & Lijun Jiang, 2022. "A New Synchronous Handling Technology of Double Stack Container Trains in Sea-Rail Intermodal Terminals," Sustainability, MDPI, vol. 14(18), pages 1-18, September.
    2. Xie, Ying & Song, Dong-Ping, 2018. "Optimal planning for container prestaging, discharging, and loading processes at seaport rail terminals with uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 119(C), pages 88-109.
    3. Behzad Behdani & Bart Wiegmans & Violeta Roso & Hercules Haralambides, 2020. "Port-hinterland transport and logistics: emerging trends and frontier research," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 22(1), pages 1-25, March.
    4. Daniela Ambrosino & Claudia Caballini, 2019. "New solution approaches for the train load planning problem," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 8(3), pages 299-325, September.
    5. Hilde Heggen & Kris Braekers & An Caris, 2018. "A multi-objective approach for intermodal train load planning," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(2), pages 341-366, March.
    6. Michał Kłodawski & Roland Jachimowski & Norbert Chamier-Gliszczyński, 2024. "Analysis of the Overhead Crane Energy Consumption Using Different Container Loading Strategies in Urban Logistics Hubs," Energies, MDPI, vol. 17(5), pages 1-24, February.
    7. Hyun Ji Park & Sung Won Cho & Abhilasha Nanda & Jin Hyoung Park, 2023. "Data-driven dynamic stacking strategy for export containers in container terminals," Flexible Services and Manufacturing Journal, Springer, vol. 35(1), pages 170-195, March.
    8. Ambrosino, Daniela & Siri, Silvia, 2015. "Comparison of solution approaches for the train load planning problem in seaport terminals," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 79(C), pages 65-82.

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