On solving biquadratic optimization via semidefinite relaxation
In this paper, we study a class of biquadratic optimization problems. We first relax the original problem to its semidefinite programming (SDP) problem and discuss the approximation ratio between them. Under some conditions, we show that the relaxed problem is tight. Then we consider how to approximately solve the problems in polynomial time. Under several different constraints, we present variational approaches for solving them and give provable estimation for the approximation solutions. Some numerical results are reported at the end of this paper. Copyright Springer Science+Business Media, LLC 2012
| Year of publication: |
2012
|
|---|---|
| Authors: | Yang, Yuning ; Yang, Qingzhi |
| Published in: |
Computational Optimization and Applications. - Springer. - Vol. 53.2012, 3, p. 845-867
|
| Publisher: |
Springer |
| Subject: | Biquadratic optimization | Quadratic optimization | SDP relaxation | Approximation algorithm |
Saved in:
Saved in favorites
Similar items by subject
-
Subtour elimination constraints imply a matrix-tree theorem SDP constraint for the TSP
Gutekunst, Samuel C., (2020)
-
Hidden integrality and semirandom robustness of SDP relaxation for sub-Gaussian mixture model
Fei, Yingjie, (2022)
-
On zero duality gap in nonconvex quadratic programming problems
Zheng, X., (2012)
- More ...
Similar items by person