eprintid: 5011
rev_number: 24
eprint_status: archive
userid: 351
dir: disk0/00/00/50/11
datestamp: 2016-01-15 02:08:16
lastmod: 2021-08-27 17:15:52
status_changed: 2016-01-15 02:08:16
type: monograph
metadata_visibility: show
item_issues_count: 2
creators_name: Ruszczynski, A.
creators_name: Swietanowski, A.
creators_id: 1475
creators_id: AL1272
title: On the Regularized Decomposition Method for Two Stage Stochastic Linear Problems
ispublished: pub
internal_subjects: iis_met
internal_subjects: iis_mod
divisions: prog_opt
abstract: A new approach to the regularized decomposition (RD) algorithm for two stage stochastic problems is presented. The RD method combines the ideas of the Dantzig-Wolfe decomposition principle and modern nonsmooth optimization methods. A new subproblem solution method using the primal simplex algorithm for linear programming is proposed and then tested on a number of large scale problems. The new approach makes it possible to use a more general problem formulation and thus allows considerably more freedom when creating the model. The computational results are highly encouraging.
date: 1996-02
date_type: published
publisher: WP-96-014
iiasapubid: WP-96-014
price: 10
creators_browse_id: 1544
creators_browse_id: 2438
full_text_status: public
monograph_type: working_paper
place_of_pub: IIASA, Laxenburg, Austria
pages: 25
coversheets_dirty: FALSE
fp7_type: info:eu-repo/semantics/book
citation:   Ruszczynski, A. <https://pure.iiasa.ac.at/view/iiasa/1544.html> & Swietanowski, A. <https://pure.iiasa.ac.at/view/iiasa/2438.html>  (1996).  On the Regularized Decomposition Method for Two Stage Stochastic Linear Problems.   IIASA Working Paper. IIASA, Laxenburg, Austria: WP-96-014     
document_url: https://pure.iiasa.ac.at/id/eprint/5011/1/WP-96-014.pdf