信任区域子问题的一阶扰动理论

IF 2.3 2区 数学 Q1 MATHEMATICS, APPLIED IMA Journal of Numerical Analysis Pub Date : 2024-07-06 DOI:10.1093/imanum/drae042
Bo Feng, Gang Wu
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引用次数: 0

摘要

信任区域子问题(TRS)是一个重要问题,出现在数值优化、Tikhonov 正则化问题和约束特征值问题等许多应用中。近几十年来,大量研究集中于如何高效解决信任区域子问题。据我们所知,关于信任区域子问题扰动分析的成果很少。为了填补这一空白,我们重点研究了信任区域子问题的一阶扰动理论。本文的主要贡献有三方面。首先,假设 TRS 处于易解状态,我们给出了扰动 TRS 仍处于易解状态的充分条件。其次,借助 TRS 的结构和经典特征问题扰动理论,对拉格朗日乘子和 TRS 的解进行一阶扰动分析,并定义其条件数。第三,我们指出,即使 TRS 处于近乎困难的情况,其解和拉格朗日乘数也可能是条件良好的。所建立的结果是可计算的,有助于事先评估大规模 TRS 问题的条件不良情况。数值实验表明了所建立的界限的尖锐性和所提出的策略的有效性。
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First-Order Perturbation Theory of Trust-Region Subproblem
Trust-region subproblem (TRS) is an important problem arising in many applications such as numerical optimization, Tikhonov regularization of ill-posed problems and constrained eigenvalue problems. In recent decades, extensive works focus on how to solve the trust-region subproblem efficiently. To the best of our knowledge, there are few results on perturbation analysis of the trust-region subproblem. In order to fill in this gap, we focus on first-order perturbation theory of the trust-region subproblem. The main contributions of this paper are three-fold. First, suppose that the TRS is in easy case, we give a sufficient condition under which the perturbed TRS is still in easy case. Secondly, with the help of the structure of the TRS and the classical eigenproblem perturbation theory, we perform first-order perturbation analysis on the Lagrange multiplier and the solution of the TRS, and define their condition numbers. Thirdly, we point out that the solution and the Lagrange multiplier could be well-conditioned even if TRS is in nearly hard case. The established results are computable, and are helpful to evaluate ill-conditioning of the large-scale TRS problem beforehand. Numerical experiments show the sharpness of the established bounds and the effectiveness of the proposed strategies.
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来源期刊
IMA Journal of Numerical Analysis
IMA Journal of Numerical Analysis 数学-应用数学
CiteScore
5.30
自引率
4.80%
发文量
79
审稿时长
6-12 weeks
期刊介绍: The IMA Journal of Numerical Analysis (IMAJNA) publishes original contributions to all fields of numerical analysis; articles will be accepted which treat the theory, development or use of practical algorithms and interactions between these aspects. Occasional survey articles are also published.
期刊最新文献
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