eprintid: 4204
rev_number: 20
eprint_status: archive
userid: 351
dir: disk0/00/00/42/04
datestamp: 2016-01-15 02:04:50
lastmod: 2021-08-27 17:14:58
status_changed: 2016-01-15 02:04:50
type: monograph
metadata_visibility: show
item_issues_count: 4
creators_name: Ruszczynski, A.
creators_id: 1475
title: On Augmented Lagrangian Decomposition Methods For Multistage Stochastic Programs
ispublished: pub
internal_subjects: iis_met
internal_subjects: iis_sys
internal_subjects: iis_cmp
internal_subjects: iis_mod
divisions: prog_opt
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 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: 1994-02
date_type: published
publisher: WP-94-005
iiasapubid: WP-94-005
price: 10
creators_browse_id: 1544
full_text_status: public
monograph_type: working_paper
place_of_pub: IIASA, Laxenburg, Austria
pages: 8
coversheets_dirty: FALSE
fp7_type: info:eu-repo/semantics/book
citation:   Ruszczynski, A. <https://pure.iiasa.ac.at/view/iiasa/1544.html>  (1994).  On Augmented Lagrangian Decomposition Methods For Multistage Stochastic Programs.   IIASA Working Paper. IIASA, Laxenburg, Austria: WP-94-005     
document_url: https://pure.iiasa.ac.at/id/eprint/4204/1/WP-94-005.pdf