Loading...
| Name: | Description: | Size: | Format: | |
|---|---|---|---|---|
| 368.15 KB | Adobe PDF |
Advisor(s)
Abstract(s)
Due to the increase in world-wide containerized cargo transport
port authorities are facing considerable pressure to increase effi-
ciency of existing facilities. Container vessels with 18, 000 TEUs (twentyfoot
equivalent units) are expected soon to create high flow peaks at
container terminals. In this paper we propose a new framework for managing
intermodal container terminals, based on the model predictive control
methodology. A model based on queues and container categorization
is used by a model predictive controller to solve the handling resource
allocation problem in a container terminal in an optimal way, while respecting
constraints on resource availability. The optimization of the operations
is performed in an integrated way for the whole terminal rather
than only for an individual subprocess. Containers are categorized into
empty and full containers, and divided in classes according to their final
destination. With more detailed information available, like container fi-
nal destination, it is possible to establish priorities for the container flows
inside the terminal. The order in which the container classes should be
loaded into a carrier can now be addressed taking into account the carrier
future route. The model ability to track the number of containers per
class makes this framework suitable for describing terminals integrated
in an intermodal transport network and a valuable tool for coordinating
the transport modal shift towards a more sustainable and reliable
transport. The potential of the proposed framework is illustrated with
simulation studies based on a high-peak flow scenario and for a long-term
scheduled scenario.
Description
Keywords
Citation
Nabais, J. & Negenborn, R. R. & Ayala Botto, M. (2012). A novel predictive control based framework for optimizing intermodal container terminal operations. In H. Hu, X. Shi, R. Stahlbock, S. Voß (eds). Lecture Notes in Computer Science, 7555 (pp. 53-71). Berlin, Germany: Springer Verlag