In this paper, we propose a new methodology for handling optimization problems with uncertain data. With the usual Robust Optimization paradigm, one looks for the decisions ensurin...
Abstract. Uncertainty, like imprecision and vagueness, has gained considerable attention the last decade. To this extend we present a preliminary report on extending the Rule Marku...
Giorgos Stoilos, Giorgos B. Stamou, Vassilis Tzouv...
Classical ontologies are not suitable to represent imprecise nor uncertain pieces of information. As a solution we will combine fuzzy Description Logics with a possibilistic layer....
Many real datasets have uncertain categorical attribute values that are only approximately measured or imputed. Uncertainty in categorical data is commonplace in many applications...
The problem of searching for important factors in a simulation model is considered when the simulation output is subject to stochastic variation. Bettonvil and Kleijnen (1996) giv...