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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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## Dataset Structure
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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
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code for running classifical solver, generate training data, evaluating neural solver: https://github.com/sunnweiwei/FrontierCO
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## Dataset Structure
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