On the numerical solution of stochastic optimization problems

Abstract

We introduce the stochastic linear programming (SLP) model classes, which will be considered in this paper, on the basis of a small-scale linear programming problem. The solutions for the various problem formulations are discussed in a comparative fashion. We point out the need for model and solution analysis. Subsequently, we outline the basic ideas of selected major algorithms for two classes of SLP problems: two-stage recourse problems and problems with chance constraints. Finally, we illustrate the computational behavior of two algorithms for large-scale SLP problems. © 2006 International Federation for Information Processing.