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English(EN) Runtime Analysis of a Compact Genetic Algorithm on a Truly Multi-valued OneMax Function

新分析改进了多值函数的遗传算法运行时

研究人员改进了应用于G-OneMax函数的多值紧凑型遗传算法(cGA)的运行时分析。新分析实现了O(n r log^3(n) log^3(r))的运行时,显著优于之前的O(n r^3 log^2(n) log(r))。该增强界限与先前针对更简单的多值函数的结果相匹配,并通过使用高级漂移定理和集中不等式来跟踪算法频率矩阵内的概率质量移动来证明。 AI

排序理由 该集群包含一篇学术论文,详细介绍了算法分析的理论改进。[lever_c_demoted from research: ic=1 ai=0.7]

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

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新分析改进了多值函数的遗传算法运行时

报道来源 [1]

  1. arXiv cs.NE (Neural & Evolutionary) TIER_1 English(EN) · Carsten Witt ·

    Runtime Analysis of a Compact Genetic Algorithm on a Truly Multi-valued OneMax Function

    Recently, the runtime analysis of multi-valued estimation-of-distribution algorithms in the framework of Ben Jedidia et al. (TCS 2024) has made significant advancements. However, almost all existing analyses are limited to multi-valued objective functions that in each dimension o…