Data error analysis in unconstrained optimization problems with the CESTAC method
This paper is concerned with the solution of optimization problems that depend on inexact data from a known distribution: how does the solution depend on the data? A method to estimate mean and standard deviation of the distribution of the solution is proposed. This method is about three times as expensive as a single optimization. The algorithm is described and a simple example is considered.
scientific article; zbMATH DE number 4096703