On Solution of Stochastic Linear Programs by Discretization Methods
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Stochastic linear programs (SLP) with complete fixed recourse are solved approximatively by means of discretization of the underlying probability distribution of the random parameters. Error estimates are given, and a priori bounds for the approximation error are derived. Furthermore, exploiting invariance properties of the probability distribution of the random parameters, problem-oriented discretizations are derived which simplify then the computation of admissible descent directions at non-stationary points.
KeywordsStochastic linear programs (SLP) discretization methods a priori error bounds invariant probability distributions
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