Approximating Global Quadratic Optimization with Convex Quadratic Constraints

被引：0
|
作者：
Yinyu Ye
机构：
[1] The University of Iowa,Department of Management Sciences
来源：
Journal of Global Optimization | 1999年 / 15卷
关键词：
Quadratic programming; Global optimizer; Approximation algorithm;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
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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页码：1 / 17
页数：16
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