Smoothing techniques and augmented lagrangian method for recourse problem of two-stage stochastic linear programming

The augmented lagrangian method can be used for solving recourse problems and obtaining their normal solution in solving two-stage stochastic linear programming problems. the augmented lagrangian objective function of a stochastic linear problem is not twice differentiable which precludes the use of a newton method. in this paper,we apply the smoothing techniques and a fast newton-armijo algorithm for solving an unconstrained smooth reformulation of this problem. computational results and comparisons are given to show the effectiveness and speed of the algorithm. © 2013 saeed ketabchi and malihe behboodi-kahoo.