On Augmented Lagrangian Decomposition Methods For Multistage Stochastic Programs
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 or decomposing it into nodes corresponding to stages. In both cases the method has favorable convergence properties and a structure which makes it convenient for parallel computing environments.
|Date of creation:||Feb 1994|
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- Alan S. Manne & Richard G. Richels, 1991. "Global CO2 Emission Reductions - the Impacts of Rising Energy Costs," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 87-108.
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- A. Ruszczynski, 1992. "Augmented Lagrangian Decomposition for Sparse Convex Optimization," Working Papers wp92075, International Institute for Applied Systems Analysis.
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