INTERIOR-POINT METHODS FOR CONVEX-PROGRAMMING

被引：45

作者：

JARRE, F

机构：

[1] Department of Operations Research, Stanford University, Stanford, 94305, CA

来源：

APPLIED MATHEMATICS AND OPTIMIZATION | 1992年 / 26卷 / 03期

关键词：

CONVEX PROGRAMMING; ELLIPSOIDAL APPROXIMATION; RELATIVE LIPSCHITZ CONDITION; SELF-CONCORDANCE;

D O I：

10.1007/BF01371086

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

This work is concerned with generalized convex programming problems, where the objective function and also the constraints belong to a certain class of convex functions. It examines the relationship of two basic conditions used in interior-point methods for generalized convex programming self-concordance and a relative Lipschitz condition-and gives a short and simple complexity analysis of an interior-point method for generalized convex programming. In generalizing ellipsoidal approximations for the feasible set, it also allows a geometrical interpretation of the analysis.

引用

页码：287 / 311

页数：25