AbstractsTransportation

The Maasvlakte port area in Rotterdam is located in the Netherlands. There are 14 container terminals and empty container depots located within this area, some are existing and some will be built in the near future. At container terminals containers are being transhipped between different modalities. At empty container depots, empty containers are being stored for a certain time. The container terminals are sharing the same customs facility and empty container depots. Transport between the container terminals and these facilities has to be organised. It is also possible that containers arrive at one container terminal, but have to depart from another container terminal. This transport between different terminals and depots is called Inter Terminal Transport (ITT). This ITT has to be organized in the future. The main question of this research is: Which transport system is most appropriate for Inter Terminal Transport between the terminals and depots at Maasvlakte 1 and 2 in 2030 and why? Previous studies were performed to determine the most appropriate transport system for ITT. This study includes a new simulation model to compare the ITT systems, in which the most up-to-date information can be used for the generation of new ITT container demand scenarios. The minimum percentage of on-time containers is set as a constraint, which was not done in previous researches. In this way a fair comparison can be made of the ITT systems and they can be evaluated using multiple criteria. In this research the AGV, ALV, and MTS will be compared. The AGV and ALV are automated vehicles, have a capacity of 2 TEU, and are expected to drive with a speed of 40 km/h in 2030. The ALV is able to load and unload containers by itself. The MTS is a manned vehicle, has a capacity of 10 TEU, and is expected to drive with a speed of 30 km/h in 2030. These ITT systems will be compared for three different economic growth scenarios (defined by the Port of Rotterdam): low growth, high oil prices, and European trend. An existing container generator (which is made in an earlier project) is used to create a table with containers. Each containers has the following properties: start time, origin (terminal/depot), delivery time, destination (terminal/depot), and size in TEU. The amount of generated containers for ITT differs per economic growth scenario: - Low growth scenario: 0.70 million containers/1.17 million TEU per year - High oil prices scenario: 0.78 million containers/1.29 million TEU per year - European trend scenario: 0.99 million containers/1.66 million TEU per year The list of containers from the generator is used as input for a simulation model. For this research a dynamic, discrete-event stochastic model has to be built. Multiple simulation software packages exist that are able to build such kind of model, but a choice has to be made. Based on the availability of the programs at the university, the costs, and the user friendliness, Simio is chosen. Containers arrive at the terminals using their start time and origin property. Containers…