CP-SynC uses coordinated LLM agents to generate, validate via synthesized checkers, and select MiniZinc models from natural language, substantially outperforming baselines on a 100-problem benchmark.
arXiv preprint arXiv:2503.10642 (2025) 37
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A survey compiling roles, applications, benchmarks, challenges, and future directions for large language models in operations research.
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CP-SynC: Multi-Agent Zero-Shot Constraint Modeling in MiniZinc with Synthesized Checkers
CP-SynC uses coordinated LLM agents to generate, validate via synthesized checkers, and select MiniZinc models from natural language, substantially outperforming baselines on a 100-problem benchmark.
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MiniOpt: Reasoning to Model and Solve General Optimization Problems with Limited Resources
MiniOpt trains LLMs under 10B parameters via RL with OptReward to model and solve general optimization problems, reporting highest average solving accuracy among comparable models.
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