Use of the "expected value solution" in linear programming under uncertainty.

by Albert Madansky

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A discussion of the uncertainty involved in most linear-programming problems in either the technology matrix, the right-hand side, or the cost. Two methods of reducing the effects of uncertainty are to replace the random elements by their expected values (the "expected-value solution"), and to replace the random elements by pessimistic estimates of their values (the "fat" technique). This paper examines the use of these methods in the one-stage stochastic linear program and describes the relation between the one- and two-stage problem. The relation between the "fat" techniques used in the one-stage problem and the so-called "slack" techniques used in the two-stage problem is then determined.

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