A New Method for Large - Scale Boxconstrained Convex Quadratic Minimizationproblems
نویسندگان
چکیده
In this paper, we present a new method for minimizing a convex quadratic function of many variables with box constraints. The new algorithm is a modiication of a method introduced recently by Friedlander and Mart nez (SIAM J. on Optimization, febru-ary 1994). Following the lines of Mor e and Toraldo (SIAM J. on Optimization 1, pp. 93-113), it combines an eecient unconstrained method with gradient projection techniques. The strategy for \leaving the current face" makes it possible to obtain convergence even when the Hessian is singular. Dual nondegeneracy is not assumed anywhere. The unconstrained minimization algorithm used within the faces was introduced by Barzilai and Borwein and analyzed by Raydan (IMA Journal on Numerical Analysis 13, pp. 321-326).
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