Abstract
We study the problem of approximating nonconvex quadratic optimization with ellipsoid constraints (ECQP) and establish a new semidefinite approximation bound, which greatly improves Tseng's result (Tseng, 2003). As an application, we strictly improve the approximation ratio for the assignment-polytope constrained quadratic program. Finally, based on a randomized algorithm, we obtain a new approximation bound for (ECQP) which is sharp in the order of the number of the ellipsoid constraints.
| Original language | English |
|---|---|
| Pages (from-to) | 378-383 |
| Number of pages | 6 |
| Journal | Operations Research Letters |
| Volume | 43 |
| Issue number | 4 |
| DOIs | |
| State | Published - 30 May 2015 |
Keywords
- Approximation algorithm
- Quadratic constrained quadratic programming
- Semidefinite programming relaxation
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