Feb, 2021
PyTorch implementation of "The Transformer Network for the Traveling Salesman Problem"
Xavier Bresson and Thomas Laurent
ArXiv : https://arxiv.org/pdf/2103.03012.pdf
Talk : https://ipam.wistia.com/medias/0jrweluovs
Slides : https://t.co/ySxGiKtQL5
# Install conda
curl -o ~/miniconda.sh -O https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh
chmod +x ~/miniconda.sh # install conda
./miniconda.sh
source ~/.bashrc
# GitHub repo
conda install git
git clone https://github.com/xbresson/TSP_Transformer.git # clone repo
cd TSP_Transformer
conda env create -f environment_gpu.yml # install python environment (CUDA 10.1)
conda activate tsp_transformer # activate environment
jupyter notebook # start jupyter notebook
- Network Training (with RTX 2080 Ti 11GB)
TSP50 (1 GPU) : Run notebook 'train_tsp_transformer_TSP50.ipynb'
TSP100 (2 GPUs) : Run notebook 'train_tsp_transformer_TSP100.ipynb' - Network Testing
TSP50 : Run notebook 'test_tsp_transformer_beamsearch_TSP50.ipynb'. Optimality gap: -0.004%.
TSP100 : Run notebook 'test_tsp_transformer_beamsearch_TSP100.ipynb'. Optimality gap: 0.371%. - Visualization
TSP50 : Run notebook 'visualization_TSP50.ipynb'
TSP100 : Run notebook 'visualization_TSP100.ipynb'