Publication at Faculty of Mathematics and Physics |
2011
Abstract
In many areas of science and engineering it is of great interest to compute different statistics under the interval uncertainty. Unfortunately, this task often turns out to be very complex.
For example, finding the bounds of the interval that includes all possible values produced by the calculation of quantities like variance or covariance for interval valued dataset is a NP-hard task. In this paper a genetic algorithm is proposed to tackle with this problem.
An application of the algorithm is presented and compared with the result of an exhaustive search using the same data, which has been performed on a grid computing infrastructure.