In [3], it is constructively demonstrated that if M is a square (not necessarily symmetric) matrix all of whose principal minors are positive, the quadratic program\[ (A1) \qquad {\text{minimize}}\quad z^T ( {Mz + q} )\quad {\text{subject to}}\quad Mz + q\geqq 0,\quad z\geqq 0, \] has an optimal solution satisfying the equation\[ ({\text{A2}})\qquad z^T ( {Mz + q} ) = 0. \]A different prooff is offered here. The analysis is then extended to programs of the form \[ ({\text{A3}})\qquad {\text{minimize}}\quad z^T W( z )\quad {\text{subject to}}\quad W( z )\geqq 0,\quad z\geqq 0, \] where W is a continuously differentiable mapping of real N-space into itself. The condition used to insure the existence of an optimal solution to (A3) is positive boundedness of the Jacobian matrix of the mapping W. Definition: A differentiable mapping $W:R^N \to R^N $ has a positively bounded Jacobian matrix, $J_w ( z )$, if there exists a real number $\delta $ such that $0 < \delta < 1$ and such that for every $z \in R^N $ each...
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