Preprint Open access
Teaching LLMs to Generate Challenging MILP Instances via Solver Feedback
Generating optimization instances that are both feasible and computationally challenging is crucial for benchmarking solvers and training learning-based optimization algorithms. Existing non-LLM generators rely on seed instances or parameter tuning, resulting in high test-time computational cost, while existing LLM gen …