ReVEL: Multi-Turn Reflective LLM-Guided Heuristic Evolution Via Structured Performance Feedback
Researchers have developed ReVEL, a system that uses large language models (LLMs) to guide the evolution of heuristics for NP-hard combinatorial optimization problems. ReVEL relies on multi-turn reflection and structured performance feedback to improve the quality of heuristics. The system has the potential to significantly improve the design of heuristics for complex optimization problems, which is a challenging and expertise-intensive task.
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