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Semidefinite relaxation and nonconvex quadratic optimization

 

作者: Yu Nesterov,  

 

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

页码: 141-160

 

ISSN:1055-6788

 

年代: 1998

 

DOI:10.1080/10556789808805690

 

出版商: Gordon and Breach Science Publishers

 

关键词: Semidefinite Optimization;Semidefinite Relaxation;Nonconvex Quadratic Optimization

 

数据来源: Taylor

 

摘要:

In this paper we study the quality of semidefinite relaxation for a global quadratic optimization problem with diagonal quadratic consraints. We prove that such relaxation approximates the exact solution of the problem with relative accuracy μ = (π/2) – 1. We consider some applications of this result

 

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