Enhanced algorithms for stochastic programming
Description:
In this dissertation, we present some of the recent advances made in solving two-stage stochastic linear programming problems of large size and complexity. Decomposition and sampling are two fundamental components of techniques to solve stochastic optimization problems. We describe improvements to the current techniques in both these areas. We studied different ways of using importance sampling techniques in the context of Stochastic programming, by varying the choice of approximation functions…
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Date:
September 1, 1993
Creator:
Krishna, A. S.
Partner:
UNT Libraries Government Documents Department