Approximating Global Quadratic Optimization with Convex Quadratic Constraints

Authors:
Yinyu Ye
Affiliations:
Department of Management Sciences, The University of Iowa, Iowa City, Iowa 52242, USA
Venue:
Journal of Global Optimization
Year:
1999

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Abstract

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.