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On the solution of two-stage linear programs under uncertainty. notes on linear programming and extensions. part 55
George B Dantzig,Albert Madansky +1 more
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TLDR
This analysis investigates the conditions under which the first-stage decisions are optimal, and formulas for using various existing computational algorithms to obtain an optimal solution are given.Abstract:
: A possible method for compensating for uncertainty in linear- programming problems is to replace the random elements by expected values or by pessimistic estimates of these values, or to recast the problem into a two-stage program so that, in the second stage, one can compensate for inaccuracies in the first stage. The purpose of this analysis is to examine the last of these methods in detail. More precisely, it investigates the conditions under which the first-stage decisions are optimal. In addition, formulas for using various existing computational algorithms to obtain an optimal solution are given.read more
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