AI RESEARCH
AutoOR: Scalably Post-training LLMs to Autoformalize Operations Research Problems
arXiv CS.LG
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ArXi:2604.16804v1 Announce Type: new Optimization problems are central to decision-making in manufacturing, logistics, scheduling, and other industrial settings. Translating complicated descriptions of these problems into solver-ready formulations requires specialized operations research (OR) expertise, making it hard to scale. We present AutoOR, a scalable synthetic data generation and reinforcement learning pipeline that trains LLMs to autoformalize optimization problems specified in natural language across linear, mixed-integer, and non-linear categories. AutoOR generates verified.