Equilibrium-Traffic-Networks
Description
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. Note: This dataset is maintained at Figshare (https://doi.org/10.6084/m9.figshare.27889251). References Article: A hybrid deep-learning-metaheuristic framework for bi-level network design problems (https://doi.org/10.1016/j.eswa.2023.122814) GitHub Repository: HDLMF_GIN-GA (https://github.com/bahmanmdd/HDLMF_GIN-GA) Primary Figshare data repository: https://doi.org/10.6084/m9.figshare.27889251
Files
Steps to reproduce
Described in the in the "Metadata.md" file, the related Github repository and the article (links below). A hybrid deep-learning-metaheuristic framework for bi-level network design problems (https://doi.org/10.1016/j.eswa.2023.122814) GitHub Repository: HDLMF_GIN-GA (https://github.com/bahmanmdd/HDLMF_GIN-GA)