Eggenberg, N., Salani, M., and Bierlaire, M. (2011)
Uncertainty Feature Optimization: an implicit paradigm for problems with noisy data, Networks 57(3):270-284.
Optimization problems with noisy data solved using stochastic programming or robust optimization approaches require the explicit characterization of an uncertainty set U that models the nature of the noise. Such approaches depend on the modeling of the uncertainty set and suffer from an erroneous estimation of the noise.
doi:10.1002/net.20428 (click here for the full paper)