Code underlying the publication: An environmentally-aware dynamic planning of electric vehicles for aircraft towing considering stochastic aircraft arrival and departure times

DOI:10.4121/041d76b2-4d2a-4db9-86d4-0dca749b2dbb.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: 10.4121/041d76b2-4d2a-4db9-86d4-0dca749b2dbb
Datacite citation style:
van Oosterom, Simon (2025): Code underlying the publication: An environmentally-aware dynamic planning of electric vehicles for aircraft towing considering stochastic aircraft arrival and departure times. Version 1. 4TU.ResearchData. software. https://doi.org/10.4121/041d76b2-4d2a-4db9-86d4-0dca749b2dbb.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Software

This repository contains the code developed for scheduling a fleet of electric towing vehicles at an airport. It accounts for the uncertainty in flight arrival/departure times by both anticipating to it (using delay probability densities) and reacting to it when it occurs. It is being made public both to act as supplementary data for publications and the PhD thesis of Simon van Oosterom, and in order for other researchers to use this repository in their own work.

History

  • 2025-02-12 first online, published, posted

Publisher

4TU.ResearchData

Format

.py, .json, .xlsx

Organizations

TU Delft, Faculty of Aerospace Engineering, Department of Control and Operations

To access the source code, use the following command:

git clone https://data.4tu.nl/v3/datasets/d1f342d6-578e-4ef1-bbc9-811648057aa9.git "etv_scheduling"

Or download the latest commit as a ZIP.