An Agent-Based Framework for the Automatic Validation of Mathematical Optimization Models

ArXi:2511.16383v2 Announce Type: replace Recently, using Large Language Models (LLMs) to generate optimization models from natural language descriptions has became increasingly popular. However, a major open question is how to validate that the generated models are correct and satisfy the requirements defined in the natural language description. In this work, we propose a novel agent-based method for automatic validation of optimization models that builds upon and extends methods from software testing to address optimization modeling.