Forecasting worldwide empty container availability with machine learning techniques

Forecasting worldwide empty container availability with machine learning techniques

Abstract Due to imbalances in the global transport of containerised goods, liner shipping companies go to great lengths to match the regional supply and demand for empty containers by transporting equipment from surplus to deficit regions. Making accurate forecasts of regional empty container availa...

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Bibliographic Details
Main Authors: Christoph Martius, Lutz Kretschmann, Miriam Zacharias, Carlos Jahn, Ole John
Format: Article
Language:English
Published: SpringerOpen 2022-07-01
Series:Journal of Shipping and Trade
Subjects:
Maritime logistics forecasts
Empty container relocation
Machine learning
Mixture density network
Online Access:https://doi.org/10.1186/s41072-022-00120-x

Internet

https://doi.org/10.1186/s41072-022-00120-x

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