Ranking based on interval-valued fuzzy predicates for social well-being analysis

PASTORE, JUAN IGNACIO; COMAS, DIEGO; BOUCHET, AGUSTINA; ACTIS DI PASQUALE, EUGENIO; MESCHINO, GUSTAVO

México DF

Workshop; International Virtual Workshop of Business Analytics Eureka 2019; 2019

OPTISAD: Mexican Network of Optimization and Decision Support System

Social well-being is one of the main goals of public policy. In this work, it is proposed a new methodology based on fuzzy predicates and interval-valued Fuzzy Logic (FL) for its computation and analysis, applied to urban areas of Argentina. The social well-being level of a territory is described using a fuzzy predicate, considering properties of different social indicators and exploiting the advantages of the interval-valued FL to deal with vague concepts. Fuzzy predicates allow to include knowledge about the meaning of social well-being and how it is traditionally measured, as well as linguistic descriptions involving relations between social indicators and social well-being. As a result, the social well-being level of each urban area is described by an interval. A method for interval comparing is also defined, in order to rank the urban areas according to their social well-being levels. Results are consistent with those obtained using the weighted average method, a known method for social well-being analysis. The approach proposed solves the problem of subjectivity in the evaluation of instances for comparative purposes, since once the fuzzy predicates are determined, the mathematical computation is the same for all the urban areas. This approach could have other interesting applications in the context of the Social Sciences, where new case studies are expected to be discovered in future work.