Abstract
In this paper optimal solutions of a stochastic programming problem are considered as functions of the underlying probability distribution. Their directional derivatives, in the sense of Gâteaux, are calculated by applying some recent results from the sensitivity analysis of nonlinear programs. These derivatives are employed as a heuristic device in order to derive the asymptotic distribution of statistical estimators of the optimal solutions.
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Shapiro, A. On differential stability in stochastic programming. Mathematical Programming 47, 107–116 (1990). https://doi.org/10.1007/BF01580855
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DOI: https://doi.org/10.1007/BF01580855