학술논문
Scenario decomposition of risk-averse multistage stochastic programming problems
Document Type
redif-article
Author
Source
Springer, Annals of Operations Research. 200(1):147-170
Subject
Language
English
Abstract
For a risk-averse multistage stochastic optimization problem with a finite scenario tree, we introduce a new scenario decomposition method and we prove its convergence. The main idea of the method is to construct a family of risk-neutral approximations of the problem. The method is applied to a risk-averse inventory and assembly problem. In addition, we develop a partially regularized bundle method for nonsmooth optimization. Copyright Springer Science+Business Media, LLC 2012