Multiple criteria decision analysis aims at representing the preferences of a decision maker over a set of alternatives; his final decision is hence the result of an aggregation process based on his preferences and the criteria set. Traditional aggregator tools such as the arithmetic mean or its weighted version generalization are still widely used -or better misused in many circumstances- since they imply, by construction, the assumption of preferential independence among criteria that in many cases is unrealistic and leads to biased result.

Fuzzy measure and Fuzzy integral is a brilliant mathematical solution to overcome this problem in that able to capture and model interaction among criteria -from redundancy to synergy- when this is the case.

The seminar introduces to audience the fundamentals of Fuzzy Measure theory and fuzzy aggregator (Choquet Integral); two specific applications in the context of composite indices are also briefly shown in all their phases raging from questionnaire design for fuzzy measure elicitation to data aggregation.