Copositive relaxation for general quadratic programming
نویسندگان
چکیده
We consider general, typically nonconvex, Quadratic Programming Problems. The Semi-deenite relaxation proposed by Shor provides bounds on the optimal solution, but it does not always provide suuciently strong bounds if linear constraints are also involved. To get rid of the linear side-constraints, another, stronger convex relaxation is derived. This relaxation uses copositive matrices. Special cases are discussed for which both relax-ations are equal. At the end of the paper, the complexity and solvability of the relaxations are discussed.
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تاریخ انتشار 1997