Sensitivity analysis of an information fusion tool: OWA operator

The successful design and application of the Ordered Weighted Averaging (OWA) method as an information fusion tool depend on the efficient computation of its order weights. The most popular methods for determining the order weights are the Fuzzy Linguistic Quantifiers approach and the Minimal Variability method which give different behavior patterns for OWA. These methods will be compared by using Sensitivity Analysis on the outputs of OWA with respect to the optimism degree of the decision maker. The theoretical results are illustrated in a water resources management problem. The Fuzzy Linguistic Quantifiers approach gives more information about the behavior of the OWA outputs in comparison to the Minimal Variability method. However, in using the Minimal Variability method, the OWA has a linear behavior with respect to the optimism degree and therefore it has better computation efficiency.