Datasets › Equilibrium-Traffic-Networks

Equilibrium-Traffic-Networks

Introduced by Bahman Madadi et al. in A hybrid deep-learning-metaheuristic framework for bi-level network design problems10 Mar 2023 archive 2025-07-28

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

References

  • Article: A hybrid deep-learning-metaheuristic framework for bi-level network design problems - Link
  • GitHub Repository: HDLMF_GIN-GA - Link
  • Primary Figshare Data Repository: Link

Note: This dataset is maintained at Figshare.

Benchmarks archive 2025-07-28

No leaderboard in the archive resolves to this dataset.

Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 1 paper for it but never published that list.

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

CC BY 4.0

Modalities archive 2025-07-28

Languages archive 2025-07-28

Variants archive 2025-07-28

  • Equilibrium-Traffic-Networks

1 variant name, as the archive lists them.

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections