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On Augmented Lagrangian Decomposition Methods For Multistage Stochastic Programs

  • A. Ruszczynski

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.

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Paper provided by International Institute for Applied Systems Analysis in its series Working Papers with number wp94005.

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Date of creation: Feb 1994
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Handle: RePEc:wop:iasawp:wp94005
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  1. 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.
  2. A. Ruszczynski, 1992. "Augmented Lagrangian Decomposition for Sparse Convex Optimization," Working Papers wp92075, International Institute for Applied Systems Analysis.
  3. Alan Manne & Richard Richels, 1992. "Buying Greenhouse Insurance: The Economic Costs of CO2 Emission Limits," MIT Press Books, The MIT Press, edition 1, volume 1, number 026213280x, June.
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