3 papers
cs.LG2026
Speeding Up Mixed-Integer Programming Solvers with Sparse Learning for Branching
Selin BayramoÄlu, George L Nemhauser, Nikolaos V Sahinidis
Machine learning is increasingly used to improve decisions within branch-and-bound algorithms for mixed-integer programming. Many existing approaches rely on deep learning, which o…
math.OC2024
Constructing Tight Quadratic Relaxations for Global Optimization: II. Underestimating Difference-of-Convex (D.C.) Functions
William R. Strahl, Arvind U. Raghunathan, Nikolaos V. Sahinidis +1
Recent advances in the efficiency and robustness of algorithms solving convex quadratically constrained quadratic programming (QCQP) problems motivate developing techniques for cre…
math.OC2024
Constructing Tight Quadratic Relaxations for Global Optimization: I. Outer-Approximating Twice-Differentiable Convex Functions
William R. Strahl, Arvind U. Raghunathan, Nikolaos V. Sahinidis +1
When computing bounds, spatial branch-and-bound algorithms often linearly outer approximate convex relaxations for non-convex expressions in order to capitalize on the efficiency a…