A Simulation Study for Evaluating a Slot Allocation Model for a Liner Shipping Network

  • Sebastian Zurheide
  • Kathrin Fischer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6971)


Revenue management (RM) methods are still only rarely used in the liner shipping industry. Usually, skilled employees make the decisions whether to accept or reject a booking and decision support systems are not commonly used. But for maximizing a company’s profit it can be crucial to make the right decisions for each booking request and therefore such a system can make an important contribution to success. In this work, a discrete-event simulation model for container bookings is developed, including a quantitative slot allocation model which takes into account different segmentations, the network structure of liner shipping with the possibility of transshipments, and the existence of different round trips of ships on the services. With a simulation study, different scenarios, networks and input settings can be evaluated regarding their performance, to determine the best strategy for the company. In this study, the incoming bookings are simulated and the decision whether a booking is to be accepted or rejected is based on the capacity that is available in the respective booking class according to the solution of the slot allocation model. This booking limit (BL) strategy is compared to a ”first come first serve” (FCFS) strategy and to an optimal strategy (OS) which is based on the assumption that all bookings are known in advance. The results show that the BL strategy is recommendable for liner shipping companies, as it leads to significant profit increases compared to FCFS.


Empty Container Liner Shipping Revenue Management Slot Allocation First Come First Serve 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Sebastian Zurheide
    • 1
  • Kathrin Fischer
    • 1
  1. 1.Hamburg University of TechnologyHamburgGermany

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