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: 10.4121/13508421

Konstantinos Gkiotsalitis (2021): A demand management and frequency settings model for complying to the COVID-19 capacity limits in public transport operations. Version 1. 4TU.ResearchData. software. https://doi.org/10.4121/13508421.v1

Software

• Ground Transport

Covid-19, demand management, frequency settings, multi-objective optimization, pandemic-imposed capacity, public transport

MIT

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Konstantinos Gkiotsalitis

Description:

This repository contains the software code and the documentation of a model that sets the frequencies of public transport lines and derives the Pareto optimal demand management strategies considering the pandemic-imposed vehicle capacities due to COVID-19.

Referencing:

In case you use this code for scientific purposes, you can cite the paper "A demand management and frequency settings model for complying to the COVID-19 capacity limits in public transport operations" once it is publicly available.

License:

MIT License

Dependencies:

Note that the script is written in Python. Running or modifying this script requires an installed version of Python 3.6. In addition, the mathematical model is solved with the use of Gurobi 9.0.3. You would need a Gurobi license to obtain an optimal solution.

To implement the model, you would need to create text files with your dataset following the provided documentation.

• 2021-01-04 first online, published, posted

4TU.ResearchData

• This software code is developed in the research programme 'COVID 19 Wetenschap voor de Praktijk', project number:10430042010018. The project is funded by the Dutch Research Organization for Health Research and Development (ZonMw)

University of Twente, Transport Engineering and Management (TEM)