Solving Cut-Generating Linear Programs via Machine Learning
Cut-generating linear programs (CGLPs) play a key role as a separation oracle to produce valid inequalities for the feasible region of optimization problems. When incorporated inside of branch-and-bound, the cutting planes obtained from CGLPs help to tighten relaxations and improve dual bounds. Running CGLPs at nodes of the branch-and-bound tree, however, is computationally cumbersome due … Read more