In this paper we develop and test scenario generation methods for asset liability management models. We propose a multi-stage stochastic programming model for a Dutch pension fund. Both randomly sampled event trees and event trees tting the mean and the covariance of the return distribution are used for generating the coeecients of the stochastic program. In order to investigate the performance...

In stochastic optimization problems, uncertainty is normally represented by means of a scenario tree. Finding an accurate representation of this uncertainty when dealing with a set of historical series is an important issue, because of its influence in the results of the above mentioned problems. This article uses a procedure to create the scenario tree divided into two phases: the first one pr...

Correctness verification of query results is a significant challenge in database outsourcing. Most of the proposed approaches impose high overhead, which makes them impractical in real scenarios. Probabilistic approaches are proposed in order to reduce the computation overhead pertaining to the verification process. In this paper, we use the notion of trust as the basis of our probabilistic app...

Motivated by the challenges encountered in sawmill production planning, we study a multi-product, multi-period production planning problem with uncertainty in the quality of raw materials and consequently in processes yields, as well as uncertainty in products demands. As demand and yield own different uncertain natures, they are modeled separately and then integrated. Demand uncertainty is con...

Multistage stochastic programs are effective for solving long-term planning problems under uncertainty. Such programs are usually based on a scenario model of future environment developments. A good approximation of the underlying stochastic process may involve a very large number of scenarios and their probabilities. We discuss the case when enough data paths can be generated, but due to solva...