Equilibrium-Traffic-Networks

This repository contains three DGL datasets 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. 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, and Anaheim) from the well-known "transport networks for research" repository.

Detailed information can be found in the "Metadata.md" file.

References

• A hybrid deep-learning-metaheuristic framework for bi-level network design problems
• GitHub Repository: HDLMF_GIN-GA