单调线性互补问题的内部点方法基于新的内核函数,并具有控制表格调整问题的应用程序
Goran Lesaja1,2, Anna Oganian3, Tifani Williams1
1Mathematical Sciences, Georgia Southern University, Statesboro, Georgia, USA.
概括
一种新的基于内核的内部点方法 (IPM) 有效地解决了单调的线性互补性问题 (LCP). 这种方法对统计披露限制模型有希望,比如连续控制表格调整 (CTA) 问题.
科学领域:
- 优化方法 优化方法
- 计算数学 计算数学 计算数学
- 数据 隐私 数据 隐私 数据
背景情况:
- 单调的线性互补性问题 (LCP) 在各个领域都是基本的.
- 解决LCP和相关问题的现有方法,如控制表格调整 (CTA) 有局限性.
- 统计披露限制 (SDL) 模型对于保护敏感的表格数据至关重要.
研究的目的:
- 引入一种基于内核的新型内部点方法 (IPM) 来解决单调的LCP.
- 为IPM开发一个新的对数障碍项和内核函数.
- 评估该方法是否适用于SDL中持续存在的CTA问题.
主要方法:
- 一种可行的基于内核的内部点方法 (IPM),使用一种新的对数屏障内核函数.
- 全球收和代边界的导出,用于短步和长步算法.
- 适用于连续控制表格调整 (CTA) 问题和随机生成的单调LCP.
主要成果:
- 拟议的IPM证明了全球趋同.
- 代边界用于短步和长步算法.
- 数值结果表明,该方法是连续CTA问题的可行选择,并且在随机LCP实例上表现良好.
结论:
- 开发的基于内核的IPM是解决单调的LCP的一个有希望的方法.
- 该方法显示了通过连续CTA问题在统计披露限制 (SDL) 中的应用潜力.
- 建议进一步进行广泛的数值研究,以充分确定算法的性能特征.
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