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Synthetically generating traffic scenarios for simulation-based container terminal planning
Citation Link: https://doi.org/10.15480/882.5156
Publikationstyp
Preprint
Date Issued
2023-06-06
Sprache
English
Author(s)
Institut
TORE-DOI
Citation
Technische Universität Hamburg (2023-06-06)
Peer Reviewed
false
More than 80 % of world trade is delivered via sea, making the maritime supply chain a very important backbone for the economy (UNCTAD 2020). Containerized trade regularly outperforms other types of transport in terms of growth, coinciding with consistent increases of average container vessel sizes (UNCTAD 2020). Container terminal operations are heavily affected by this development, since less but larger port calls create unwanted peaks and stress on the terminals and the hinterland. Not all container terminals are affected equally by the described situation. Economic cycles and events such as the global COVID-19 pandemic or the Russian war in Ukraine change the global supply chains, trade characteristics and transport demands between ports in the world.
In 2004, Hartmann proposed an approach to create scenarios for simulation and optimization in the sense of container terminal planning and logistics. Due to the significant changes in maritime trade over the years, a new approach for generating synthetic container flow data became practical. In 2021, we introduced a rethought and reworked approach on this topic.The proposed tool, named ConFlowGen, aims to assist planners, scientists, and other maritime experts with providing comprehensive container flow scenarios based on minimal inputs and assumptions of the user. In this paper, we introduce ConFlowGen's general principle of operation in an exemplary use case in the context of container terminal planning.
In 2004, Hartmann proposed an approach to create scenarios for simulation and optimization in the sense of container terminal planning and logistics. Due to the significant changes in maritime trade over the years, a new approach for generating synthetic container flow data became practical. In 2021, we introduced a rethought and reworked approach on this topic.The proposed tool, named ConFlowGen, aims to assist planners, scientists, and other maritime experts with providing comprehensive container flow scenarios based on minimal inputs and assumptions of the user. In this paper, we introduce ConFlowGen's general principle of operation in an exemplary use case in the context of container terminal planning.
Subjects
Container Terminal
Terminal Planning
Economic Traffic Forecast
Synthetic Data
Traffic Scenario Generation
DDC Class
330: Wirtschaft
380: Handel, Kommunikation, Verkehr
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PIANC_AGA_2023_DPWA_Kastner_and_Grasse.pdf
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