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MP
2006

Conditional Value-at-Risk in Stochastic Programs with Mixed-Integer Recourse

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Conditional Value-at-Risk in Stochastic Programs with Mixed-Integer Recourse
In classical two-stage stochastic programming the expected value of the total costs is minimized. Recently, mean-risk models - studied in mathematical finance for several decades - have attracted attention in stochastic programming. We consider Conditional Value-at-Risk as risk measure in the framework of two-stage stochastic integer programming. The paper addresses structure, stability, and algorithms for this class of models. In particular, we study continuity properties of the objective function, both with respect to the first-stage decisions and the integrating probability measure. Further, we present an explicit mixed-integer linear programming formulation of the problem when the probability distribution is discrete and finite. Finally, a solution algorithm based on Lagrangean relaxation of nonanticipativity is proposed. Key words. Stochastic programming
Rüdiger Schultz, Stephan Tiedemann
Added 14 Dec 2010
Updated 14 Dec 2010
Type Journal
Year 2006
Where MP
Authors Rüdiger Schultz, Stephan Tiedemann
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