Graph neural networks for job shop scheduling problems: A survey

Igor G. Smit, Jianan Zhou, Robbert Reijnen, Yaoxin Wu, Jian Chen, Cong Zhang, Zaharah Bukhsh, Yingqian Zhang, Wim Nuijten

Abstract: Highlights•Survey graph neural networks for job-shop and flow-shop scheduling problems.•Summarize graph representations and GNN architectures for solving JSSPs and FSPs.•Analyze drawbacks of GNN-based methods and discuss future research directions.