On Augmented Lagrangian Decomposition Methods For Multistage Stochastic Programs

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/3987 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/3987 http://eprints.org/relation/isCoversheetVersionOf https://pure.iiasa.ac.at/id/document/3987 archive 351 disk0/00/00/42/04 2016-01-15 02:04:50 2021-08-27 17:14:58 2016-01-15 02:04:50 monograph show 4 Ruszczynski A. 1475 On Augmented Lagrangian Decomposition Methods For Multistage Stochastic Programs pub iis_met iis_sys iis_cmp iis_mod prog_opt 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. 1994-02 published WP-94-005 WP-94-005 10 1544 public working_paper IIASA, Laxenburg, Austria 8 FALSE info:eu-repo/semantics/book