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README.md

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 **FrontierCO** is a curated benchmark suite for evaluating ML-based solvers on large-scale and real-world **Combinatorial Optimization (CO)** problems. The benchmark spans **8 classical CO problems** across **5 application domains**, providing both training and evaluation instances specifically designed to test the frontier of ML and LLM capabilities in solving NP-hard problems.
 
-Combinatorial optimization plays a fundamental role in discrete mathematics, computer science, and operations research, with applications in routing, scheduling, allocation, and more. As ML-based solvers evolve—ranging from neural networks to symbolic reasoning with large language models—**FrontierCO** offers the first comprehensive dataset suite tailored to test these solvers at realistic scales and difficulties.
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 code for evaluating agent https://github.com/sunnweiwei/CO-Bench?tab=readme-ov-file#evaluation-on-frontierco
 
 code for running classifical solver, generate training data, evaluating neural solver: https://github.com/sunnweiwei/FrontierCO