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

Naomi Miller () and Andrzej Ruszczynski ()
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Naomi Miller: RUTCOR, Rutgers University, Piscataway, New Jersey 08854

Operations Research, 2011, vol. 59, issue 1, 125-132

Abstract: 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.

Keywords: stochastic programming; risk; two-stage models; decomposition (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (14)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:oropre:v:59:y:2011:i:1:p:125-132

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