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.
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页码：1475 / 1490
页数：16
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