其他摘要：In this contribution an iterative method for solving the nonlinear minimization problem with equality constraints is presented. The method is based on the sequential minimization of the differential penalization function known as augmented Lagrangian. In order to solve the unconstrained minimization subproblems a conjugate gradients tecnique combined with a trust region estrategy of globalization is used, which is especially efficient for large scale problems. The preliminary numerical experiments show that the outwardly ill condictioning of the subproblems can be avoid with a simple technique.
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