eprintid: 4541
rev_number: 22
eprint_status: archive
userid: 351
dir: disk0/00/00/45/41
datestamp: 2016-01-15 02:06:11
lastmod: 2021-08-27 17:15:19
status_changed: 2016-01-15 02:06:11
type: monograph
metadata_visibility: show
item_issues_count: 2
creators_name: Kiwiel, K.
creators_name: Rosa, C.H.
creators_name: Ruszczynski, A.
creators_id: 1545
creators_id: 1475
title: Decomposition via Alternating Linearization
ispublished: pub
internal_subjects: iis_met
internal_subjects: iis_sys
divisions: prog_opt
abstract: A new approximate proximal point method for minimizing the sum of two convex functions is introduced. It replaces the original problem by a sequence of regularized subproblems in which the functions are alternately represented by linear models. The method updates the linear models and the prox center, as well as the prox coefficient. It is monotone in terms of the objective values and converges to a solution of the problem, if any. A dual version of the method is derived and analyzed. Applications of the methods to multistage stochastic programming problems are discussed and preliminary numerical experience presented.
date: 1995-06
date_type: published
publisher: WP-95-051
iiasapubid: WP-95-051
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: 25
coversheets_dirty: FALSE
fp7_type: info:eu-repo/semantics/book
citation:   Kiwiel, K., Rosa, C.H. <https://pure.iiasa.ac.at/view/iiasa/1541.html>, & Ruszczynski, A. <https://pure.iiasa.ac.at/view/iiasa/1544.html>  (1995).  Decomposition via Alternating Linearization.   IIASA Working Paper. IIASA, Laxenburg, Austria: WP-95-051     
document_url: https://pure.iiasa.ac.at/id/eprint/4541/1/WP-95-051.pdf