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English(EN) Mycelial Search: A Graph-Structured Metaheuristic for Continuous Optimisation

菌丝搜索:一种新的用于连续优化的图结构元启发式算法

研究人员推出了一种新颖的图结构元启发式算法——菌丝搜索(Myco),专为连续优化问题设计。Myco利用活跃尖端、社区加权流、自适应弦可塑性和锚定注入等概念来管理信息共享和搜索方向。在CEC 2022基准套件上的评估表明,Myco在特定函数上取得了有竞争力的结果,而消融研究突出了社区结构和弦可塑性在调节信息交换和方向影响方面的重要性。 AI

影响 引入了一种新颖的图结构方法用于连续优化,有望提高在复杂景观上的性能。

排序理由 该集群包含一篇详细介绍新优化算法的研究论文。

在 arXiv cs.NE (Neural & Evolutionary) 阅读 →

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菌丝搜索:一种新的用于连续优化的图结构元启发式算法

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该集群包含一篇详细介绍新优化算法的研究论文。
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报道来源 [2]

  1. arXiv cs.AI TIER_1 English(EN) · Mohammad Mahdi Dehshibi ·

    菌丝体搜索:一种用于连续优化的图结构元启发式算法

    arXiv:2608.23323v1 Announce Type: cross Abstract: Continuous optimisation methods need to balance sharing information and maintaining alternative search directions. In this paper, we introduce Mycelial Search (Myco), a graph-structured metaheuristic designed around active tips, c…

  2. arXiv cs.NE (Neural & Evolutionary) TIER_1 English(EN) · Mohammad Mahdi Dehshibi ·

    菌丝体搜索:一种用于连续优化的图结构元启发式算法

    Continuous optimisation methods need to balance sharing information and maintaining alternative search directions. In this paper, we introduce Mycelial Search (Myco), a graph-structured metaheuristic designed around active tips, community-weighted flow, adaptive cord plasticity, …