An interior-point smoothing technique for Lagrangian relaxation in large-scale convex programming

被引：2
|
作者：
Shida, Masayuki [1 ]
机构：
[1] Natl Def Acad, Dept Math, Yokosuka, Kanagawa 2398686, Japan
来源：
OPTIMIZATION | 2008年 / 57卷 / 01期
关键词：
convex programming; Lagrangian relaxation; interior-point method; globally self-concordant family;
D O I：
10.1080/02331930701779096
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：
An interior-point smoothing technique for Lagrangian relaxation in large-scale convex programming is discussed. We consider the general convex program formulated in the conic form. For the problem, we define the perturbed Lagrangian relaxation by using the self-concordant barriers, and show the basic properties of the perturbed problems. Based on the properties, we present a conceptual method which numerically traces the trajectory that leads to the optimal solution of the original problem.
引用
收藏
页码：183 / 200
页数：18
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