Second-order lower bounds on the expectation of a convex function
We develop a class of lower bounds on the expectation of a convex function. The bounds utilize the first two moments of the underlying random variable, whose support is contained in a bounded interval or hyper-rectangle. Our bounds have applications to stochastic programs whose random parameters are known only through limited moment information. Computational results are presented for two-stage stochastic linear programs.
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