A new augmented Lagrangian approach to duality and exact penalization

被引：3
|
作者：
Lalitha, C. S. [1 ]
机构：
[1] Univ Delhi, Rajdhani Coll, Dept Math, New Delhi 110075, India
来源：
JOURNAL OF GLOBAL OPTIMIZATION | 2010年 / 46卷 / 02期
关键词：
Augmented Lagrangian; Augmenting function; Nonconvex problem; Duality; FRAMEWORK;
D O I：
10.1007/s10898-009-9420-4
中图分类号：
C93 [管理学]; O22 [运筹学];
学科分类号：
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要：
In this paper, we introduce a new notion of augmenting function known as indicator augmenting function to establish a minmax type duality relation, existence of a path of solution converging to optimal value and a zero duality gap relation for a nonconvex primal problem and the corresponding Lagrangian dual problem. We also obtain necessary and sufficient conditions for an exact penalty representation in the framework of indicator augmented Lagrangian.
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页码：233 / 245
页数：13
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