  When additional information sources are available in decision making problems
that allow stochastic optimization formulations, an important question is how
to optimally use the information the sources are capable of providing. A
framework that relates information accuracy determined by the source's
knowledge structure to its relevance determined by the problem being solved was
proposed in a companion paper. There, the problem of optimal information
acquisition was formulated as that of minimization of the expected loss of the
solution subject to constraints dictated by the information source knowledge
structure and depth. Approximate solution methods for this problem are
developed making use of probability metrics method and its application for
scenario reduction in stochastic optimization.
