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Inventory-based dispatching of automated guided vehicles on container terminals

In: Container Terminals and Cargo Systems

Author

Listed:
  • Dirk Briskorn

    (Christian-Albrechts-Universität zu Kiel)

  • Andreas Drexl

    (Christian-Albrechts-Universität zu Kiel)

  • Sönke Hartmann

    (HPC Hamburg Port Consulting GmbH
    HHLA Container Terminal Altenwerder GmbH)

Abstract

This paper deals with automated guided vehicles (AGVs) which transport containers between the quay and the stack on automated container terminals. The focus is on the assignment of transportation jobs to AGVs within a terminal control system operating in real time. First, we describe a rather common problem formulation based on due times for the jobs and solve this problem both with a greedy priority rule based heuristic and with an exact algorithm. Subsequently, we present an alternative formulation of the assignment problem, which does not include due times. This formulation is based on a rough analogy to inventory management and is solved using an exact algorithm. The idea behind this alternative formulation is to avoid estimates of driving times, completion times, due times, and tardiness because such estimates are often highly unreliable in practice and do not allow for accurate planning. By means of simulation, we then analyze the different approaches. We show that the inventory-based model leads to better productivity on the terminal than the due-time-based formulation.

Suggested Citation

  • Dirk Briskorn & Andreas Drexl & Sönke Hartmann, 2007. "Inventory-based dispatching of automated guided vehicles on container terminals," Springer Books, in: Kap Hwan Kim & Hans-Otto Günther (ed.), Container Terminals and Cargo Systems, pages 195-214, Springer.
    • Handle: RePEc:spr:sprchp:978-3-540-49550-5_10
    DOI: 10.1007/978-3-540-49550-5_10
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    Citations

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    Cited by:

    1. Luo, Jiabin & Wu, Yue, 2015. "Modelling of dual-cycle strategy for container storage and vehicle scheduling problems at automated container terminals," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 79(C), pages 49-64.
    2. Roy, D. & de Koster, M.B.M., 2015. "Stochastic Modeling of Unloading and Loading Operations at a Container Terminal using Automated Lifting Vehicles," ERIM Report Series Research in Management ERS-2015-005-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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