papersSEP 12 04:00 UTC
MAPLE pairs LLM planning with evolutionary search for optimization modeling
A new arXiv paper introduces MAPLE, a memory-augmented planning method that combines language models with an evolutionary search process. The work targets optimization tasks, where business users often understand their constraints but lack operations-research expertise or dedicated support. It builds on the idea of LLM-based optimization agents that convert natural-language requirements into models or solver programs.