Hybrid models for learning to branch
A recent Graph Neural Network (GNN) approach for learning to branch has been shown to successfully reduce the running time of branch-and-bound (B&B) algorithms for Mixed Integer Linear Programming (MILP). While the GNN relies on a GPU for inference, MILP solvers are purely CPU-based. This severe...
| Main Authors: | , , , , , |
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| Format: | Conference item |
| Language: | English |
| Published: |
Conference on Neural Information Processing Systems
2020
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