Journal of Global Optimization

, Volume 15, Issue 1, pp 1–17

Approximating Global Quadratic Optimization with Convex Quadratic Constraints

  • Yinyu Ye

DOI: 10.1023/A:1008370723217

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


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

Copyright information

© Kluwer Academic Publishers 1999

Authors and Affiliations

  • Yinyu Ye
    • 1
  1. 1.Department of Management SciencesThe University of IowaIowa CityUSA