Branching Strategies Based on Subgraph GNNs: A Study on Theoretical Promise versus Practical Reality

Junru Zhou, Yicheng Wang, Pan Li

Graph Neural Networks (GNNs) have emerged as a promising approach for ``learning to branch'' in Mixed-Integer Linear Programming (MILP). While standard Message-Passing GNNs (MPNNs)…