Please run the cells in notebooks/osmnx_generator.ipynb
to enable generation
of graph inputs from OSMnx -- this may take a few minutes.
Code for all experiments can be found in the /notebooks/
directory. Experiment
files follow the naming convention "exp_[experiment name]". GNN and greedy-t
hyperparameter tuning can be found in /notebooks/gnn_tuner.ipynb
and
/notebooks/greedy_tuner.ipynb
, respectively.
/gnn_library/
contains all information relevant to defining, training, testing,
and saving GNN models. Several pre-trained models can be loaded from
`/trained_models/'. The experiments contain many examples of loading
these models.
Finally, instance_generator.py
is used for the generation of OBBM instances
of different graph configurations, torch_converter.py
gives code for
converting instances into PyG representations, evaluate.py
contains code
for estimating average competitive ratio for learned models, and algorithms.py
contains implementations of baseline algorithms.