eprintid: 4089
rev_number: 22
eprint_status: archive
userid: 351
dir: disk0/00/00/40/89
datestamp: 2016-01-15 02:04:03
lastmod: 2021-08-27 17:14:45
status_changed: 2016-01-15 02:04:03
type: monograph
metadata_visibility: show
item_issues_count: 4
creators_name: Rosa, C.H.
creators_name: Ruszczynski, A.
creators_id: 1545
creators_id: 1475
title: On Augmented Lagrangian Decomposition Methods for Multistage Stochastic Programs
ispublished: pub
internal_subjects: iis_cmp
internal_subjects: iis_met
internal_subjects: iis_sys
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 and by decomposing it into nodes corresponding to stages. Theoretical convergence properties of the two approaches are derived and a computational illustration is presented.
date: 1994-12
date_type: published
publisher: WP-94-125
iiasapubid: WP-94-125
price: 10
creators_browse_id: 1541
creators_browse_id: 1544
full_text_status: public
monograph_type: working_paper
place_of_pub: IIASA, Laxenburg, Austria
pages: 23
coversheets_dirty: FALSE
fp7_type: info:eu-repo/semantics/book
citation:   Rosa, C.H. <https://pure.iiasa.ac.at/view/iiasa/1541.html> & 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-94-125     
document_url: https://pure.iiasa.ac.at/id/eprint/4089/1/WP-94-125.pdf