Maximization of a PSD quadratic form and factorization

被引:1
|
作者
Hladik, Milan [1 ]
Hartman, David [2 ,4 ]
Zamani, Moslem [3 ]
机构
[1] Charles Univ Prague, Dept Appl Math, Fac Math & Phys, Malostranske Nam 25, Prague 11800, Czech Republic
[2] Czech Acad Sci, Inst Comp Sci, Prague, Czech Republic
[3] Ferdowsi Univ Mashhad, Dept Appl Math, Fac Math Sci, Mashhad, Razavi Khorasan, Iran
[4] Charles Univ Prague, Inst Comp Sci, Fac Math & Phys, Prague 11800, Czech Republic
关键词
Convex quadratic form; Concave programming; NP-hardness; Upper bound; Maximum norm; Preconditioning; APPROXIMATION;
D O I
10.1007/s11590-020-01624-w
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
We consider the problem of maximization of a convex quadratic form on a convex polyhedral set, which is known to be NP-hard. In particular, we focus on upper bounds on the maximum value. We investigate utilization of different vector norms (estimating the Euclidean one) and different objective matrix factorizations. We arrive at some kind of duality with positive duality gap in general, but with possibly tight bounds. We discuss theoretical properties of these bounds and also extensions to generally preconditioned factors. We employ mainly the maximum vector norm since it yields efficiently computable bounds, however, we study other norms, too. Eventually, we leave many challenging open problems that arose during the research.
引用
收藏
页码:2515 / 2528
页数:14
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