Learning Topological Representations with Bidirectional Graph Attention Network for Solving Job Shop Scheduling Problem
Paper: https://arxiv.org/abs/2402.17606
If you make use of the code/experiment or TBGAT algorithm in your work, please cite our paper (Bibtex below).
@InProceedings{zhanglearning2024,
title = {Learning Topological Representations with Bidirectional Graph Attention Network for Solving Job Shop Scheduling Problem},
author = {Zhang, Cong and Cao, Zhiguang and Wu, Yaoxin and Song, Wen and Sun, Jing},
booktitle = {Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence},
year = {2024},
}
python 3.9.x
cuda 10.2 + torch 1.10.0
pip3 install torch==1.10.0 torchvision==0.11.0 torchaudio===0.10.0 -f https://download.pytorch.org/whl/cu102/torch_stable.html
Install dependencies:
pip install --upgrade pip
pip install torch-scatter==2.0.9 -f https://pytorch-geometric.com/whl/torch-1.10.0+cu102.html
pip install torch-sparse==0.6.12 -f https://pytorch-geometric.com/whl/torch-1.10.0+cu102.html
pip install torch-geometric==2.0.3
pip install matplotlib==3.4.3
pip install ortools==9.3.10497
pip install openpyxl
Clone this repo and within the repo folder run the following command.
Create image neural-tabu-jssp-image:
docker build -t neural-tabu-jssp-image .
Create container neural-tabu-jssp-container from neural-tabu-jssp-image, and activate it:
docker run --gpus all --name neural-tabu-jssp-container -it neural-tabu-jssp-image