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English(EN) Random Walk on Bézier Curves for Global Optimization

新的 Bézier 游走演化框架通过自适应几何增强优化

研究人员推出了一种新颖的优化框架 Bézier Walk Evolution (BWE),该框架使用由几何驱动的自适应轨迹构建。该方法将 Bézier 曲线与随机游走机制相结合,以平衡元启发式优化中的探索和利用。BWE 的自适应曲线阶数允许从广泛的全局搜索平滑过渡到集中的局部精炼,为传统的受自然启发的(优化)设计提供了一种可解释的替代方案。在基准函数和工程问题上的实验表明,与 L-SHADE 和 CMA-ES 等现有优化器相比,BWE 具有强大的性能和可扩展性。 AI

排序理由 该条目是一篇研究论文,详细介绍了一个新的优化框架。[lever_c_demoted from research: ic=1 ai=1.0]

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

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新的 Bézier 游走演化框架通过自适应几何增强优化

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该条目是一篇研究论文,详细介绍了一个新的优化框架。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.NE (Neural & Evolutionary) TIER_1 English(EN) · Yuansheng Gao ·

    Bézier 曲线上的随机游走用于全局优化

    Balancing exploration and exploitation remains a central challenge in metaheuristic optimization. To address this issue, this paper proposes Bézier Walk Evolution (BWE), a geometry-driven optimization framework that reformulates evolutionary search as adaptive trajectory construc…