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English(EN) AGDN: Learning to Solve Traveling Salesman Problem with Anisotropic Graph Diffusion Network

新的AGDN框架为旅行商问题提供了改进的解决方案

研究人员开发了各向异性图扩散网络(AGDN),这是一种新颖的图神经网络,旨在解决旅行商问题(TSP)。AGDN通过使用MixScore转移矩阵和各向异性图扩散策略来改进信息交换,从而解决了利用图结构方面的挑战。实验表明,AGDN在各种实例大小和分布的TSP求解方面优于现有方法,同时保持了具有竞争力的计算时间和良好的泛化能力。 AI

影响 这种新的网络架构可能为复杂的物流和优化问题带来更有效的解决方案。

排序理由 该集群包含一篇研究论文,详细介绍了使用图神经网络解决组合优化问题的新方法。

在 arXiv cs.LG 阅读 →

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报道来源 [2]

  1. arXiv cs.LG TIER_1 English(EN) · Bolin Shen, Ziwei Huang, Zhiguang Cao, Yushun Dong ·

    AGDN: Learning to Solve Traveling Salesman Problem with Anisotropic Graph Diffusion Network

    arXiv:2606.19185v1 Announce Type: new Abstract: The Traveling Salesman Problem (TSP) is a cornerstone of combinatorial optimization and arises in many practical scenarios. Although graph-based learning approaches have been explored for TSP, the question of how to exploit graph st…

  2. arXiv cs.LG TIER_1 English(EN) · Yushun Dong ·

    AGDN: Learning to Solve Traveling Salesman Problem with Anisotropic Graph Diffusion Network

    The Traveling Salesman Problem (TSP) is a cornerstone of combinatorial optimization and arises in many practical scenarios. Although graph-based learning approaches have been explored for TSP, the question of how to exploit graph structure more effectively remains open. We presen…