The relation between stochasticity and terminal stacking performance of import containers

The relation between stochasticity and terminal stacking performance of import containers: A simulation study

Mutters, Nienke (TU Delft Civil Engineering and Geosciences)

Verbraeck, Alexander (mentor)
Huang, Yilin (graduation committee)
Duinkerken, Mark (graduation committee)

Delft University of Technology

Transport, Infrastructure and Logistics

2019-04-18

With an increase in amount of container terminals competition between terminals has risen. Therefore it has become more and more important for terminal operators to conduct their work as efficient as possible. Efficient terminal operations are hindered by stochasticity, which is defined as random variation in parameter values. Due to missing information on exact arrival times, requested containers are often stored underneath other containers, which will then need to be reshuffled to reach the requested container. This reshuffling is performed while a hinterland transport mode is waiting for the requested container and therefore increases service times and SC utilisation during peak
hours. This research investigates the relation between stochasticity and terminal stacking performance of import containers with a simulation model. Terminal stacking performance is subdivided into the Key Performance Indicators reshuffles per retrieval, truck service time and maximum straddle carrier utilisation per hour. The results show that implementing housekeeping moves can spare the entire import yard up to 639 764 reshuffles per year, 8 854 hours in truck serving per year and 8 minute per peak hour per SC. Even in the experiments where the level of stochasticity is high, a saving of 120 656 reshuffles per year, 883 hours truck service time and 3 minutes per SC peak hour are observed. The higher the level of stochasticity, the smaller the improvement on the KPIs is. Lastly, it can be concluded that stacking performance also deteriorates when the level of stochasticity becomes higher.

Container terminal
Stacking operations
Stochasticity
Discrete Event Simulation

http://resolver.tudelft.nl/uuid:46743128-dd15-4811-8893-60792bd969cc

Student theses

master thesis

© 2019 Nienke Mutters