ReVEL: Multi-Turn Reflective LLM-Guided Heuristic Evolution Via Structured Performance Feedback
Researchers have developed a new method for designing effective heuristics for NP-hard combinatorial optimization problems. The approach, called ReVEL, uses large language models to guide the evolution of heuristics through structured performance feedback. This work has the potential to significantly improve the development of more efficient heuristics for complex optimization problems.
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