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Smoothing Techniques and Augmented Lagrangian Method for Recourse Problem of Two‐Stage Stochastic Linear Programming

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Listed:
  • Saeed Ketabchi
  • Malihe Behboodi-Kahoo

Abstract

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.

Suggested Citation

  • Saeed Ketabchi & Malihe Behboodi-Kahoo, 2013. "Smoothing Techniques and Augmented Lagrangian Method for Recourse Problem of Two‐Stage Stochastic Linear Programming," Journal of Applied Mathematics, John Wiley & Sons, vol. 2013(1).
    • Handle: RePEc:wly:jnljam:v:2013:y:2013:i:1:n:735916
    DOI: 10.1155/2013/735916
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    References listed on IDEAS

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    1. Julia L. Higle & Suvrajeet Sen, 1991. "Stochastic Decomposition: An Algorithm for Two-Stage Linear Programs with Recourse," Mathematics of Operations Research, INFORMS, vol. 16(3), pages 650-669, August.
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