Omkar2118/datasets huggingface dataset:
Equilibrium-Traffic-Networks

This repository contains three graph datasets for the UE traffic assignment problem on Sioux-Falls, Eastern-Massachusetts and Anaheim networks in both dgl and pyg formats. The datasets are generated and used to train and evaluate models for solving the User Equilibrium (UE) problem on three transportation networks:

- ** Sioux-Falls**

- ** Eastern-Massachusetts**

- **Anaheim **

These networks are sourced from the well-known  *"transport networks for research"*  repository.

These datasets are generated for the study **"A hybrid deep-learning-metaheuristic framework for bi-level network design problems"** by Bahman Madadi and Gonçalo H. de Almeida Correia, published in *Expert Systems with Applications*. 

## Metadata
Detailed information can be found in the  `Metadata.md`  file.

## Links
- **Figshare Dataset Repository**: [Link](https://doi.org/10.6084/m9.figshare.27889251)

## References
- **Article**: *A hybrid deep-learning-metaheuristic framework for bi-level network design problems* - [Link](https://doi.org/10.1016/j.eswa.2023.122814)
- **GitHub Repository**: *HDLMF_GIN-GA* - [Link](https://github.com/bahmanmdd/HDLMF_GIN-GA)
- **Primary Figshare Data Repository**: [Link](https://doi.org/10.6084/m9.figshare.27889251)

Note: This dataset is maintained at [Figshare](https://doi.org/10.6084/m9.figshare.27889251).

Introducing paper: A hybrid deep-learning-metaheuristic framework for bi-level network design problems