In this paper, the augmented Lagrangian method is investigated for solving recourse problems and obtaining their normal solution in solving two-stage stochastic linear programming problems. The objective function of stochastic linear programming problem is piecewise linear and non-differentiable. Therefore, to use a smooth optimization methods, the objective function is approximated by a differentiable and piecewise quadratic function. Using quadratic approximation, it is required to obtain the least 2-norm solution for many linear programming problems in each iteration. To obtain the least 2-norm solution for inner problems based on the augmented Lagrangian method, the generalized Newton method is applied.