arXiv AI By Cuong Van Duc, Minh Nguyen Dinh Tuan, Tam Vu Duc, Tung Vu Duy, Son Nguyen Van, Hanh Nguyen Thi, Binh Huynh Thi Thanh

ReVEL: Multi-Turn Reflective LLM-Guided Heuristic Evolution via Structured Performance Feedback

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arXiv AI
Sep 7

OR-Agent: Bridging Evolutionary Search and Structured Research for Automated Heuristic Design

OR-Agent is a multi‑agent research framework that automates heuristic design for optimization problems by structuring heuristic search as a tree‑based workflow with explicit hypothesis generation and systematic backtracking. It introduces a hierarchical, optimization‑inspired reflection system that uses short‑term reflections as verbal gradients, long‑term reflections as verbal momentum, and memory compression as semantic weight decay to guide research dynamics. Experiments on classical combinatorial optimization tasks and simulation‑based cooperative driving scenarios show that OR‑Agent outperforms strong evolutionary search baselines, with all code and data publicly available.

By Qi Liu, Ruochen Hao, Can Li, Wanjing Ma