Improving constants of strong convexity in linear stochastic programming |
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Affiliation: | Faculty of Mathematics, University of Duisburg-Essen, Campus Essen, Thea-Leymann-Str. 9, D-45127 Essen, Germany |
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Abstract: | We derive formulas for constants of strong convexity (CSCs) of expectation functions encountered in two-stage stochastic programs with linear recourse. One of them yields a CSC as the optimal value of a certain quadratically constrained quadratic program, another one in terms of the thickness of the feasibility polytope of the dual problem associated to the recourse problem. CSCs appear in Hoelder-type estimates relating the distance of optimal solution sets of stochastic programs to a suitable distance of underlying probability distributions. |
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Keywords: | Stochastic programming Linear recourse Strong convexity |
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