We investigate the quality of solutions obtained from sample-average approximations to two-stage stochastic linear programs with recourse. We use a recently developed software tool executing on a computational grid to solve many large instances of these problems, allowing us to obtain high-quality solutions and to verify optimality and near-optimality of the computed solutions in various ways.
Citation
Optimization Technical Report 02-01, Computer Sciences Department, University of Wisconsin-Madison, January, 2002. Revised September, 2002.
Article
View The Empirical Behavior of Sampling Methods for Stochastic Programming