Journal
MATHEMATICS OF OPERATIONS RESEARCH
Volume 30, Issue 3, Pages 662-677Publisher
INFORMS
DOI: 10.1287/moor.1040.0136
Keywords
stochastic programming approximations; generalized moment problems
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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 hyperrectangle. 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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