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Copositive realxation for genera quadratic programming

 

作者: A.J. Quist,   E. De klerk,   C. Roos,   T. Terlaky,  

 

期刊: Optimization Methods and Software  （Taylor Available online 1998）
卷期: Volume 9, issue 1-3  

页码: 185-208

 

ISSN:1055-6788

 

年代: 1998

 

DOI:10.1080/10556789808805692

 

出版商: Gordon and Breach Science Publishers

 

关键词: Copositive Matrics;Quadratic Programming;Global Optimization;Duality Theory;Semi-definite Optimiztion;Shor Relaxation

 

数据来源: Taylor

 

摘要:

We consider general, typically nonconvex, Quadratic programming Problem. The Semidefinite relaxation proposed by Shor provides bounds on the optimal solution, but it does not always provide sufficiently strong bounds if linear constraintare also involved. To get rid of the linear side-constraints, another, stronger convex relaxation is derved. This relaxation uses copositive matrices. Special cases are dicussed for which both relaxations are equal. At end of the paper, the complexity and solvablility of the relaxation are discussed.

 

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