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GenOR-Twin: A Semantic Middleware for Integrating Operational Discourse with Mathematical Optimization

arXiv · AI, language, vision and robotics · article · Sep 11, 2026 · UTC

We introduce GenOR-Twin, a neuro-symbolic framework that bridges the translation gap between unstructured operational logs and rigorous mathematical optimization. Our architecture uniquely positions Large Language Models as semantic translators rather than direct solvers, ensuring that the system retains the feasibility guarantees of exact combinatorial methods. { \color{red}We design a dynamic constraint injection mechanism (the runtime translation of qualitative disruption events into formal mathematical constraints) that allows the system to structurally modify the optimization problem's fe

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