Best ellipsoidal relaxation to solve a nonconvex problem
作者:
Highlights:
•
摘要
We present a new ellipsoidal relaxation of 0–1 quadratic optimization problems. The relaxation and the dual problem are derived. Both these problems are strictly feasible; so strong duality holds, and they can be solved numerically using primal-dual interior-point methods.Numerical results are presented which indicate that the described relaxation is efficient.
论文关键词:Quadratic Boolean programming,Quadratic programming,Ellipsoidal relaxation,Semidefinite programming
论文评审过程:Received 22 December 2001, Revised 7 January 2003, Available online 27 October 2003.
论文官网地址:https://doi.org/10.1016/j.cam.2003.08.012