A DATA-INDEPENDENT DISTANCE TO INFEASIBILITY FOR LINEAR CONIC SYSTEMS

被引：1
|
作者：
Pena, Javier [1 ]
Roshchina, Vera [2 ]
机构：
[1] Carnegie Mellon Univ, Tepper Sch Business, Pittsburgh, PA 15213 USA
[2] Univ South Wales, Sch Math & Stat, Sydney, NSW 2052, Australia
来源：
SIAM JOURNAL ON OPTIMIZATION | 2020年 / 30卷 / 02期
基金：
澳大利亚研究理事会;
关键词：
condition number; conic programming; distance to infeasibility; convex duality; CONDITION NUMBER; COMPLEXITY THEORY; ALGORITHM; GEOMETRY; PROJECTION;
D O I：
10.1137/18M1189464
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
We offer a unified treatment of distinct measures of well-posedness for homogeneous conic systems. To that end, we introduce a distance to infeasibility based entirely on geometric considerations of the elements defining the conic system. Our approach sheds new light on and connects several well-known condition measures for conic systems, including Renegar's distance to infeasibility, the Grassmannian condition measure, a measure of the most interior solution, and other geometric measures of symmetry and of depth of the conic system.
引用
收藏
页码：1049 / 1066
页数：18
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