Journal of Global Optimization

, Volume 15, Issue 1, pp 1–17

Approximating Global Quadratic Optimization with Convex Quadratic Constraints

Authors

  • Yinyu Ye
    • Department of Management SciencesThe University of Iowa
Article

DOI: 10.1023/A:1008370723217

Cite this article as:
Ye, Y. Journal of Global Optimization (1999) 15: 1. doi:10.1023/A:1008370723217

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.

Quadratic programmingGlobal optimizerApproximation algorithm
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Copyright information

© Kluwer Academic Publishers 1999