On augmented Lagrangian decomposition methods for multistage stochastic programs |
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Authors: | Charles H. Rosa Andrzej Ruszczyński |
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Affiliation: | (1) International Institute for Applied Systems Analysis, A-2361 Laxenburg, Austria |
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Abstract: | A general decomposition framework for large convex optimization problems based on augmented Lagrangians is described. The approach is then applied to multistage stochastic programming problems in two different ways: by decomposing the problem into scenarios and by decomposing it into nodes corresponding to stages. Theoretical convergence properties of the two approaches are derived and a computational illustration is presented. |
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Keywords: | Stochastic programming decomposition augmented Lagrangian Jacobi method parallel computation |
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