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首页> 外文期刊>SIAM Journal on Matrix Analysis and Applications >ROUNDOFF-ERROR-FREE BASIS UPDATES OF LU FACTORIZATIONS FOR THE EFFICIENT VALIDATION OF OPTIMALITY CERTIFICATES
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ROUNDOFF-ERROR-FREE BASIS UPDATES OF LU FACTORIZATIONS FOR THE EFFICIENT VALIDATION OF OPTIMALITY CERTIFICATES

机译:LU因素化的无错误的基础更新,以获得最优证书的有效验证

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摘要

The roundoff-error-free (REF) LU and Cholesky factorizations, combined with the REF substitution algorithms, allow rational systems of linear equations to be solved exactly and efficiently by working entirely in integer arithmetic. These REF computational tools share two key properties: their constituent divisions are exact, and their matrix entries' bit-lengths (i.e., required number of storage bits) are bounded polynomially. However, as this paper explains, updating the REF factorizations via the common delete-insert-reduce approach turns out to be inefficient in terms of operand bit-length growth and increased computational effort. In fact, we prove that this inefficiency can eliminate the computational savings expected of the factorization update process. Hence, the current work develops REF update algorithms that differ significantly from their traditional counterparts. To achieve this, it introduces the frame matrix methodology for representing and applying the REF factorizations, and then it devises new REF operations and shortcuts for transitioning between nearby frame matrices. The presented push-and-swap update approach utilizes these transitions to preserve the special structure of the REF factorizations and to avoid additional growth in their matrix entries' bit-lengths; this update process requires the expected O(n(2)) operations. The featured updates are column addition, deletion, and replacement with respect to the REF LU factorization. We also prove that analogous row updates can be performed via the column updates and discuss special considerations for updating the REF Cholesky factorization. An accompanying set of computational tests attests that for fully dense random instances, the push-and-swap column replacement update for the REF LU factorization is on average an order of magnitude faster than the corresponding delete-insert-reduce update for the exact rational arithmetic LU factorization. Altogether, the REF update algorithms represent a promising preliminary step toward enhancing the basic solution validation subroutines employed by state-of-the-art mixed-precision methodologies for exact linear and mixed-integer programming.
机译:通过完全在整数算术中工作,允许REF替换算法与REF替换算法结合使用的循环无差错(REF)LU和Cholesky Imputionations,允许完全且有效地解决线性方程。这些REF计算工具共享两个关键属性:它们的构成分区精确,它们的矩阵条目的比特长度(即,所需数量的存储位)被界界多项式。然而,正如本文解释所示,通过常见的删除 - 插入 - 减少方法更新ref因素,在操作数位长度的增长和增加的计算工作方面,效率低下。事实上,我们证明这种低效率可以消除预期的分解更新过程的计算节约。因此,目前的工作开发了从传统对应物中显着不同的参考更新算法。为此,它介绍了表示和应用Ref因子的帧矩阵方法,然后它为附近帧矩阵之间的转换提供了新的Ref操作和快捷方式。所提出的推送和交换更新方法利用这些过渡来保留ref因素的特殊结构,并避免其矩阵条目的比特长度额外增长;此更新过程需要预期的O(n(2))操作。特色更新是针对REF LU分解的列添加,删除和替换。我们还证明可以通过列更新执行类似的行更新,并讨论更新REF Cholesky分解的特殊考虑因素。随附的计算测试集证明,对于完全密集的随机实例,REF LU分解的按钮拨号更新平均比相应的Rational算法更新更快的速度速度快lu因分分解。总之,REF更新算法代表了一个有希望的初步步骤,旨在增强最先进的混合精密方法,用于精确线性和混合整数编程所采用的最先进的混合精密方法。

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