Data underlying Ph.D. thesis: Large set of graphs and timeseries of supply chain simulation model

DOI:10.4121/adf4373c-7a9a-4d9c-a1ff-0f893d8d0b06.v1
The DOI displayed 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/adf4373c-7a9a-4d9c-a1ff-0f893d8d0b06

Datacite citation style

van Schilt, Isabelle (2024): Data underlying Ph.D. thesis: Large set of graphs and timeseries of supply chain simulation model. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/adf4373c-7a9a-4d9c-a1ff-0f893d8d0b06.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

This data is part of the Ph.D. thesis of Isabelle M. van Schilt, Delft University of Technology.


Data includes the time series data of the synthetic counterfeit PPE supply chain discrete event simulation model. This time series data is used for the paper of structural uncertainty and the quality diversity (QD) algorithm.


Also, the data includes the decision variables dictionary for both papers. These are two dictionaries in .pkl format that include 40.000 randomly generated graphs with real-world port data for the case study. One dictionary is sorted on betweenness, and the other (QD) on the density of the network. Following, a database example of 50.000 randomly generated graphs (without real-world data) has been included in this data.

History

  • 2024-07-22 first online, published, posted

Publisher

4TU.ResearchData

Format

csv/pkl

Organizations

TU Delft, Faculty of Technology, Policy and Management, Department of Multi-Actor Systems (MAS)

DATA

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