不等式约束优化的低阶精确惩罚函数的平滑逼近。

IF 1.6 3区 数学 Q1 Mathematics
Journal of Inequalities and Applications Pub Date : 2018-01-01 Epub Date: 2018-06-11 DOI:10.1186/s13660-018-1723-x
Shujun Lian, Nana Niu
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引用次数: 1

摘要

对于不等式约束优化问题,首先提出了一种新的低阶精确惩罚函数的光滑化方法,然后证明了通过求解光滑低阶精确惩罚问题的全局解可以得到原问题的近似全局解。提出了一种基于光滑低阶精确罚函数的算法。在较温和的条件下证明了算法的全局收敛性。数值实验表明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Smoothing approximation to the lower order exact penalty function for inequality constrained optimization.

Smoothing approximation to the lower order exact penalty function for inequality constrained optimization.

Smoothing approximation to the lower order exact penalty function for inequality constrained optimization.

Smoothing approximation to the lower order exact penalty function for inequality constrained optimization.

For inequality constrained optimization problem, we first propose a new smoothing method to the lower order exact penalty function, and then show that an approximate global solution of the original problem can be obtained by solving a global solution of a smooth lower order exact penalty problem. We propose an algorithm based on the smoothed lower order exact penalty function. The global convergence of the algorithm is proved under some mild conditions. Some numerical experiments show the efficiency of the proposed method.

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来源期刊
Journal of Inequalities and Applications
Journal of Inequalities and Applications MATHEMATICS, APPLIED-MATHEMATICS
CiteScore
3.30
自引率
6.20%
发文量
136
审稿时长
3 months
期刊介绍: The aim of this journal is to provide a multi-disciplinary forum of discussion in mathematics and its applications in which the essentiality of inequalities is highlighted. This Journal accepts high quality articles containing original research results and survey articles of exceptional merit. Subject matters should be strongly related to inequalities, such as, but not restricted to, the following: inequalities in analysis, inequalities in approximation theory, inequalities in combinatorics, inequalities in economics, inequalities in geometry, inequalities in mechanics, inequalities in optimization, inequalities in stochastic analysis and applications.
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