Augmented Lagrangian method for recourse problem of two-stage stochastic linear programming
Kybernetika, Tome 49 (2013) no. 1, pp. 188-198.

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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.
Classification : 90C05, 90C15, 90C20
Keywords: two-stage stochastic linear programming; recourse problem; normal solution; augmented Lagrangian method
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     author = {Ketabchi, Saeed and Behboodi-Kahoo, Malihe},
     title = {Augmented {Lagrangian} method for recourse problem of two-stage stochastic linear programming},
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     language = {en},
     url = {http://geodesic.mathdoc.fr/item/KYB_2013__49_1_a13/}
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Ketabchi, Saeed; Behboodi-Kahoo, Malihe. Augmented Lagrangian method for recourse problem of two-stage stochastic linear programming. Kybernetika, Tome 49 (2013) no. 1, pp. 188-198. http://geodesic.mathdoc.fr/item/KYB_2013__49_1_a13/