2 papers
cs.AI2026
FrontierOR: Benchmarking LLMs' Capacity for Efficient Algorithm Design in Large-Scale Optimization
Minwei Kong, Chonghe Jiang, Ao Qu +24
Large language models (LLMs) are increasingly used for optimization modeling and solver-code generation, yet practical operations research and optimization problems often require a…
cs.AI2026
Automated Reformulation of Robust Optimization via Memory-Augmented Large Language Models
Jinbiao Chen, Shuang Jin, Guoyun Zhang +3
Robust optimization (RO) provides a principled framework for decision-making under uncertainty, but its practical use is often limited by the need to manually reformulate uncertain…