Inexact restoration for minimization with inexact evaluation both of the objective function and the constraints

IF 2.2 2区 数学 Q1 MATHEMATICS, APPLIED
L. Bueno, F. Larreal, J. Martínez
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引用次数: 4

Abstract

In a recent paper an Inexact Restoration method for solving continuous constrained optimization problems was analyzed from the point of view of worst-case functional complexity and convergence. On the other hand, the Inexact Restoration methodology was employed, in a different research, to handle minimization problems with inexact evaluation and simple constraints. These two methodologies are combined in the present report, for constrained minimization problems in which both the objective function and the constraints, as well as their derivatives, are subject to evaluation errors. Together with a complete description of the method, complexity and convergence results will be proved.
目标函数和约束条件均不精确的最小化不精确恢复
本文从最坏情况下泛函复杂度和收敛性的角度分析了求解连续约束优化问题的非精确恢复方法。另一方面,在不同的研究中,采用不精确恢复方法来处理具有不精确评估和简单约束的最小化问题。本报告将这两种方法结合起来,以解决目标函数和约束及其衍生物都可能产生评价误差的受限最小化问题。并对该方法进行了完整的描述,证明了该方法的复杂性和收敛性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Mathematics of Computation
Mathematics of Computation 数学-应用数学
CiteScore
3.90
自引率
5.00%
发文量
55
审稿时长
7.0 months
期刊介绍: All articles submitted to this journal are peer-reviewed. The AMS has a single blind peer-review process in which the reviewers know who the authors of the manuscript are, but the authors do not have access to the information on who the peer reviewers are. This journal is devoted to research articles of the highest quality in computational mathematics. Areas covered include numerical analysis, computational discrete mathematics, including number theory, algebra and combinatorics, and related fields such as stochastic numerical methods. Articles must be of significant computational interest and contain original and substantial mathematical analysis or development of computational methodology.
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