The global convergence of augmented Lagrangian methods based on NCP function in constrained nonconvex optimization

被引：4
|
作者：
Wu, H. X. [2 ]
Luo, H. Z. [1 ]
Li, S. L. [1 ]
机构：
[1] Zhejiang Univ Technol, Dept Appl Math, Hangzhou 310032, Zhejiang, Peoples R China
[2] Hangzhou Dianzi Univ, Dept Math, Hangzhou 310018, Peoples R China
来源：
APPLIED MATHEMATICS AND COMPUTATION | 2009年 / 207卷 / 01期
基金：
中国国家自然科学基金;
关键词：
Nonconvex optimization; Constrained optimization; Augmented Lagrangian methods; Convergence to KKT point; Degenerate point; ZERO DUALITY GAP; MULTIPLIER METHOD; GENERAL CONSTRAINTS; SADDLE-POINTS; ALGORITHM; CONVEXIFICATION; EXISTENCE;
D O I：
10.1016/j.amc.2008.10.015
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
In this paper, we present the global convergence properties of the primal-dual method using a class of augmented Lagrangian functions based on NCP function for inequality constrained nonconvex optimization problems. We construct four modified augmented Lagrangian methods based on different algorithmic strategies. We show that the convergence to a KKT point or a degenerate point of the original problem can be ensured without requiring the boundedness condition of the multiplier sequence. (C) 2008 Elsevier Inc. All rights reserved.
引用
收藏
页码：124 / 134
页数：11
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