Robust two-stage stochastic linear programs with moment constraints
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We consider the two-stage stochastic linear programming model, in which the recourse function is a worst case expected value over a set of probabilistic distributions. These distributions share the same first- and second-order moments. By using duality of semi-infinite programming and assuming knowledge on extreme points of the dual polyhedron of the constraints, we show that a deterministic equivalence of the two-stage problem is a second-order cone optimization problem. Numerical examples are presented to show non-conservativeness and computational advantage of this approach.
This is an Author's Accepted Manuscript of an article published in Optimization: A Journal of Mathematical Programming and Operations Research (2014), copyright Taylor & Francis, available online at: <a href="http://www.tandfonline.com/10.1080/02331934.2014.906598">http://www.tandfonline.com/10.1080/02331934.2014.906598</a>
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