| Abstract: | Stochastic linear programming (SLP) models involve multivariate integrals. Although in the discretely distributed case these integrals become sums they typically contain a large amount of terms. The purpose of this paper is twofold:On the one hand we discuss the usage of bounds concerning integrals for constructing SLP algorithms and secondly we point out the role of bounds-based algorithms for solving SLP problems. The conceptual considerations are demonstrated in the last section by computational results. The tests have been carried out by utilizing SLP-IOR, our model management system for SLP |
