AI RESEARCH
EvoOpt-LLM: Evolving industrial optimization models with large language models
arXiv CS.AI
•
ArXi:2602.01082v2 Announce Type: replace Optimization modeling via mixed-integer linear programming (MILP) is fundamental to industrial planning and scheduling, yet translating natural-language requirements into solver-executable models and maintaining them under evolving business rules remains highly expertise-intensive. While large language models (LLMs) offer promising avenues for automation, existing methods often suffer from low data efficiency, limited solver-level validity, and poor scalability to industrial-scale problems.