KKT SOLUTION AND CONIC RELAXATION FOR SOLVING QUADRATICALLY CONSTRAINED QUADRATIC PROGRAMMING PROBLEMS

被引：36

作者：

Lu, Cheng ^{[1
]}

Fang, Shu-Cherng ^{[2
]}

Jin, Qingwei ^{[2
]}

Wang, Zhenbo ^{[1
]}

Xing, Wenxun ^{[1
]}

机构：

[1] Tsinghua Univ, Dept Math Sci, Beijing 100084, Peoples R China

[2] N Carolina State Univ, Dept Ind & Syst Engn, Raleigh, NC 27606 USA

来源：

SIAM JOURNAL ON OPTIMIZATION | 2011年 / 21卷 / 04期

基金：

美国国家科学基金会; 中国国家自然科学基金;

关键词：

quadratically constrained quadratic programming; conic programming; global optimality condition; solvable condition; GLOBAL OPTIMALITY; CANONICAL DUALITY; OPTIMIZATION; APPROXIMATION; MINIMIZATION; BINARY; CONES;

D O I：

10.1137/100793955

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

To find a global optimal solution to the quadratically constrained quadratic programming problem, we explore the relationship between its Lagrangian multipliers and related linear conic programming problems. This study leads to a global optimality condition that is more general than the known positive semidefiniteness condition in the literature. Moreover, we propose a computational scheme that provides clues of designing effective algorithms for more solvable quadratically constrained quadratic programming problems.

引用

页码：1475 / 1490

页数：16

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