TY - JOUR
T1 - An ADMM algorithm for two-stage stochastic programming problems
AU - Arpón, Sebastián
AU - Homem-de-Mello, Tito
AU - Pagnoncelli, Bernardo K.
N1 - Publisher Copyright:
© 2019, Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2020/3/1
Y1 - 2020/3/1
N2 - The alternate direction method of multipliers (ADMM) has received significant attention recently as a powerful algorithm to solve convex problems with a block structure. The vast majority of applications focus on deterministic problems. In this paper we show that ADMM can be applied to solve two-stage stochastic programming problems, and we propose an implementation in three blocks with or without proximal terms. We present numerical results for large scale instances, and extend our findings for risk averse formulations using utility functions.
AB - The alternate direction method of multipliers (ADMM) has received significant attention recently as a powerful algorithm to solve convex problems with a block structure. The vast majority of applications focus on deterministic problems. In this paper we show that ADMM can be applied to solve two-stage stochastic programming problems, and we propose an implementation in three blocks with or without proximal terms. We present numerical results for large scale instances, and extend our findings for risk averse formulations using utility functions.
UR - http://www.scopus.com/inward/record.url?scp=85076099702&partnerID=8YFLogxK
U2 - 10.1007/s10479-019-03471-0
DO - 10.1007/s10479-019-03471-0
M3 - Article
AN - SCOPUS:85076099702
SN - 0254-5330
VL - 286
SP - 559
EP - 582
JO - Annals of Operations Research
JF - Annals of Operations Research
IS - 1-2
ER -