CVRP solver with Multi Heads Attention

TensorFlow2 and PyTorch implementation of ATTENTION, LEARN TO SOLVE ROUTING PROBLEMS!(Kool et al. 2019)(https://arxiv.org/pdf/1803.08475.pdf)

Description

Slide Share -- CVRP solver with Multi Heads Attention --

Dependencies

• Python >= 3.6
• TensorFlow >= 2.0
• PyTorch = 1.5
• tqdm
• scipy
• numpy
• plotly (only for plotting)
• matplotlib (only for plotting)

Usage

First move to "PyTorch" or "TensorFlow2" dir.

cd PyTorch

Then, generate the pickle file contaning hyperparameter values by running the following command.

python config.py

you would see the pickle file in "Pkl" dir. now you can start training the model.

python train.py -p Pkl/***.pkl

Plot prediction of the pretrained model

python plot.py -p Weights/***.pt(or ***.h5)

If you want to verify your model, you can use opensource dataset in "OpenData" dir.

Opensource data is obtained from Augerat et al.(1995)

please refer to Capacitated VRP Instances by NEO Research Group

python plot.py -p Weights/***.pt -t ../OpenData/A-n***.txt

Reference

• https://github.com/wouterkool/attention-learn-to-route
• https://github.com/d-eremeev/ADM-VRP
• https://qiita.com/ohtaman/items/0c383da89516d03c3ac0