Arbeitspapier

Inventory based dispatching of automated guided vehicles on container terminals

This paper deals with automated guided vehicles (AGVs) which transport containers between the quai and the stack on automated container terminals. The focus is on the assigment 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 dates 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 dates. 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 dates 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 date based formulation.

Language
Englisch

Bibliographic citation
Series: Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel ; No. 596

Classification
Management
Subject
Container logistics
container terminal
automated guided vehicles
simulation
Innerbetrieblicher Transport
Containerterminal
Logistikdienstleister
Automatisierung
Scheduling-Verfahren
Theorie

Event
Geistige Schöpfung
(who)
Briskorn, Dirk
Drexl, Andreas
Hartmann, Sönke
Event
Veröffentlichung
(who)
Universität Kiel, Institut für Betriebswirtschaftslehre
ZBW – Leibniz Information Centre for Economics
(where)
Kiel
(when)
2005

Handle
Last update
10.03.2025, 11:42 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • Briskorn, Dirk
  • Drexl, Andreas
  • Hartmann, Sönke
  • Universität Kiel, Institut für Betriebswirtschaftslehre
  • ZBW – Leibniz Information Centre for Economics

Time of origin

  • 2005

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