Article ID: | iaor20113622 |
Volume: | 59 |
Issue: | 1 |
Start Page Number: | 125 |
End Page Number: | 132 |
Publication Date: | Jan 2011 |
Journal: | Operations Research |
Authors: | Ruszczyski Andrzej, Miller Naomi |
Keywords: | programming: linear |
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.