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On the identification of local minimizers in inertia-controlling methods for quadratic programming. (English) Zbl 0737.65047
For the general quadratic nonconvex programming problem: minimize $$\varphi(x)=c^ Tx+{1\over 2} x^ T Hx$$ subject to $$Ax\geq\beta$$, where the Hessian matrix is symmetric and $$A$$ is an $$m\times n$$ matrix, the verification of optimality is discussed within the context of an inertia- controlling method. A computational method is derived that will attempt to determine if a dead point is a local minimizer.

##### MSC:
 65K05 Numerical mathematical programming methods 90C20 Quadratic programming
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