A discussion of the uncertainty in most linear-programming problems, an uncertainty that is found in either the technology matrix, the right-hand side, or the cost. Some of the more usual methods of reducing the effects of uncertainty are those of (1) replacing the random elements by their expected values, (2) replacing the random elements by pessimistic estimates of their values, and (3) recasting the problem into a two-stage problem in which, in the second stage, the "inaccuracies" can be compensated for in the first-stage activities. These methods are called the expected-value solution, the "fat" solution, and the "slack" solution, respectively. This paper examines the one-stage linear program under uncertainty, indicating the relation between these various "solutions."
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