Risk-Averse Two-Stage Stochastic Linear Programming: Modeling and Decomposition

• 成果类型: Article
• 署名作者: Miller, Naomi; Ruszczynski, Andrzej
• 署名单位: Rutgers University System; Rutgers University New Brunswick; Rutgers University System; Rutgers University New Brunswick
• 刊物名称: OPERATIONS RESEARCH
• ISSN/ISSBN: 0030-364X
• DOI: 10.1287/opre.1100.0847
• 发表日期: 2011
• 页码: 125-132
• 关键词: mixed-integer recourse; dominance

摘要

We formulate a risk-averse two-stage stochastic linear programming problem in which unresolved uncertainty remains after the second stage. The objective function is formulated as a composition of conditional risk measures. We analyze properties of the problem and derive necessary and sufficient optimality conditions. Next, we construct a new decomposition method for solving the problem that exploits the composite structure of the objective function. We illustrate its performance on a portfolio optimization problem.