Data underlying the PhD dissertation: Real-time Co-planning in Synchromodal Transport Networks using Model Predictive Control

doi: 10.4121/19761784.v1
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/19761784
Datacite citation style:
Larsen, Rie (2022): Data underlying the PhD dissertation: Real-time Co-planning in Synchromodal Transport Networks using Model Predictive Control. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/19761784.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset

This dataset is a collection of the results and the data behind the figures displayed in the PhD dissertation `Real-time Co-planning in Synchromodal Transport Networks using Model Predictive Control'. The research presented in this dissertation provides insights into how container transport can realistically be planned at the operational level in real-time when several different stakeholders own the vehicles.


history
  • 2022-05-13 first online, published, posted
publisher
4TU.ResearchData
format
zip-files containing matlab figures and .mat tables
funding
  • Complexity Methods for Predictive Synchromodality (Comet-PS) (grant code 439.16.120) [more info...] Dutch Research Council
organizations
TU Delft, Faculty of Mechanical, Maritime and Materials Engineering (3mE), Department of Maritime and Transport Technology (M&TT)

DATA

files (5)