Algorithms Based upon Generalized Linear Programming for Stochastic Programs with Recourse

Nazareth, J.L. (1984). Algorithms Based upon Generalized Linear Programming for Stochastic Programs with Recourse. IIASA Working Paper. IIASA, Laxenburg, Austria: WP-84-081

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Abstract

In this paper, the author discusses solution algorithms for a particular form of two-stage stochastic linear programs with recourse. The algorithms considered are based upon the generalized linear programming method of Wolfe.

The author first gives an alternative formulation of the original problem and uses this to examine the relation between tenders and certainty equivalents. He then considers problems with simple recourse, discussing algorithms for two cases: (a) when the distribution is discrete and probabilities are known explicitly; (b) when the probability distribution is other than discrete or when it is only known implicitly through some simulation model. The latter case is especially useful because it makes possible the transition to general recourse. Some possible solution strategies based upon generalized programming for general recourse problems are then discussed.

This paper is a product of the Adaptation and Optimization Project within the System and Decision Sciences Program.

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