An optimal algorithm and superrelaxation for minimization of a quadratic function subject to separable convex constraints with applications
The authors consider bound constrained quadratic programming problems of the following form: \[ \min_{x\in\Omega} (x^T Ax- x^T b), \] where \(A\) denotes a symmetric positive definite matrix and \(\Omega\) a closed convex set defined by convex differentiable function of the following form \[ \Omega= \Omega_1\times\cdots \times \Omega_s\quad\text{and}\quad \Omega_i= \{x_i\in R^{1_i}: h_i(x_i)\leq 0\},\quad i= 1,\dots,s. \] For this problems, the authors present a new algorithm which is a modification of an earlier algorithm of the authors. -- Numerical experiments are presented.
scientific article; zbMATH DE number 6093768
scientific article