ReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolution Haoran Y e

Neural Information Processing Systems 

The omnipresence of NP-hard combinatorial optimization problems (COPs) compels domain experts to engage in trial-and-error heuristic design. The long-standing endeavor of design automation has gained new momentum with the rise of large language models (LLMs).

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