Approximating Global Quadratic Optimization with Convex Quadratic Constraints
- Yinyu Ye
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We consider the problem of approximating the global maximum of a quadratic program (QP) subject to convex non-homogeneous quadratic constraints. We prove an approximation quality bound that is related to a condition number of the convex feasible set; and it is the currently best for approximating certain problems, such as quadratic optimization over the assignment polytope, according to the best of our knowledge.
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- Approximating Global Quadratic Optimization with Convex Quadratic Constraints
Journal of Global Optimization
Volume 15, Issue 1 , pp 1-17
- Cover Date
- Print ISSN
- Online ISSN
- Kluwer Academic Publishers
- Additional Links
- Quadratic programming
- Global optimizer
- Approximation algorithm
- Industry Sectors
- Yinyu Ye (1)
- Author Affiliations
- 1. Department of Management Sciences, The University of Iowa, Iowa City, Iowa, 52242, USA