Learning Discrete Decisions for MIPs with Constraint-Aware Diffusion

Excerpt

arXiv:2608.13079v2 Announce Type: replace Abstract: This paper proposes a novel learning-based approach to approximately solve instances of mixed-integer optimization problems. These problems are computationally challenging, as they require jointly determining discrete and continuous decisions while satisfying complex combinatorial constraints. The proposed method relies on a graph-based generative diffusion model that learns the discrete component of mixed-integer optimization problems while in