3 papers
math.OC2026
Learning to Choose Branching Rules for Nonconvex MINLPs
Timo Berthold, Fritz Geis
Outer-approximation-based branch-and-bound is a common algorithmic framework for solving MINLPs (mixed-integer nonlinear programs) to global optimality, with branching variable sel…
math.OC2026
Global Optimization for Combinatorial Geometry Problems Revisited in the Era of LLMs
Timo Berthold, Dominik Kamp, Gioni Mexi +2
Recent progress in LLM-driven algorithm discovery, exemplified by DeepMind's AlphaEvolve, has produced new best-known solutions for a range of hard geometric and combinatorial prob…
math.OC2024
Cut-based Conflict Analysis in Mixed Integer Programming
Gioni Mexi, Felipe Serrano, Timo Berthold +2
For almost two decades, mixed integer programming (MIP) solvers have used graph-based conflict analysis to learn from local infeasibilities during branch-and-bound search. In this…