KKT Solution and Conic Relaxation for Solving Quadratically Constrained Quadratic Programming Problems

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 positi...

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Vydáno v:SIAM journal on optimization Ročník 21; číslo 4; s. 1475 - 1490
Hlavní autoři: Lu, Cheng, Fang, Shu-Cherng, Jin, Qingwei, Wang, Zhenbo, Xing, Wenxun
Médium: Journal Article
Jazyk:angličtina
Vydáno: Philadelphia Society for Industrial and Applied Mathematics 01.10.2011
Témata:
Algorithms
Approximation
Optimization
Quadratic programming
ISSN:1052-6234, 1095-7189
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Shrnutí: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. [PUBLICATION ABSTRACT]
Bibliografie:ObjectType-Article-1
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ISSN:1052-6234
1095-7189
DOI:10.1137/100793955