yining043 / DIFUSCO

Code for "DIFUSCO: Graph-based Diffusion Solvers for Combinatorial Optimization"

DIFUSCO: Graph-based Diffusion Solvers for Combinatorial Optimization

See "DIFUSCO: Graph-based Diffusion Solvers for Combinatorial Optimization" for the paper associated with this codebase.

Setup

conda env create -f environment.yml
conda activate difusco

Running TSP experiments requires installing the additional cython package for merging the diffusion heatmap results:

cd difusco/utils/cython_merge
python setup.py build_ext --inplace
cd -

Codebase Structure

• difusco/pl_meta_model.py: the code for a meta pytorch-lightning model for training and evaluation.
• difusco/pl_tsp_model.py: the code for the TSP problem
• difusco/pl_mis_model.py: the code for the MIS problem
• difusco/trian.py: the handler for training and evaluation

Data

Please check the data folder.

Reproduction

Please check the reproducing_scripts for more details.

Pretrained Checkpoints

Please download the pretrained model checkpoints from here.

Reference

If you found this codebase useful, please consider citing the paper:

@article{sun2023difusco,
  title={DIFUSCO: Graph-based Diffusion Solvers for Combinatorial Optimization},
  author={Sun, Zhiqing and Yang, Yiming},
  journal={arXiv preprint arXiv:2302.08224},
  year={2023}
}