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English(EN) RefineEvo: Planning-Guided Heuristic Evolution with Bidirectional Experience

RefineEvo框架增强了优化问题的启发式设计

研究人员推出了一种新的演化框架RefineEvo,旨在增强组合优化问题的自动启发式设计(AHD)。该系统利用规划器动态管理演化算子,并利用反射器在双向经验池中存储经验教训。实验表明,RefineEvo在解的质量和令牌效率方面优于现有方法,实现了更自主的启发式设计。 AI

影响 该框架可能导致更高效、更自主地设计复杂优化任务的启发式方法。

排序理由 该集群包含一篇详细介绍新研究框架的学术论文。

在 arXiv cs.CL 阅读 →

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RefineEvo框架增强了优化问题的启发式设计

报道来源 [2]

  1. arXiv cs.CL TIER_1 English(EN) · Yang Wu, Junran Pan, Yifan Zhang, Ning Xu, Fanshuo Zeng, Jian Cheng ·

    RefineEvo: Planning-Guided Heuristic Evolution with Bidirectional Experience

    arXiv:2607.11358v1 Announce Type: new Abstract: Automatic Heuristic Design (AHD) has emerged as a transformative approach for solving combinatorial optimization problems. While recent Large Language Model (LLM)-based methods have shown promise, they predominantly rely on fixed ev…

  2. arXiv cs.CL TIER_1 English(EN) · Jian Cheng ·

    RefineEvo:具有双向经验的引导式启发式演化

    Automatic Heuristic Design (AHD) has emerged as a transformative approach for solving combinatorial optimization problems. While recent Large Language Model (LLM)-based methods have shown promise, they predominantly rely on fixed evolutionary operators and struggle to effectively…