The codes for the paper published in JMS named 'Solving task scheduling problems in cloud manufacturing via attention mechanism and deep reinforcement learning'.
This repository is a minimal implementation of SAM. Parts of the codes are from 'https://github.com/wouterkool/attention-learn-to-route.git'.
The core idea is to improve the scheduling performance for the task scheduling in cloud manufacturing with the attention mechanism. Detailed motivations and introductions can be found in our paper as listed above.
If you find something valueable in our work, please cite the refference as follows:
@article{wang2022solving, title={Solving task scheduling problems in cloud manufacturing via attention mechanism and deep reinforcement learning}, author={Wang, Xiaohan and Zhang, Lin and Liu, Yongkui and Zhao, Chun and Wang, Kunyu}, journal={Journal of Manufacturing Systems}, volume={65}, pages={452--468}, year={2022}, publisher={Elsevier} }
The detailed definitions of the DRL environment are in './agent_AM/problems/schedule/state_schedule.py'
GOOD LUCK FOR YOUR RESEARCH!