A Fuzzy Qualitative Evaluation System: A multi-granular aggregation approach using fuzzy compound linguistic variable
Measuring qualitative attributes is a complex process which includes imprecise decisions for designing, rating, and quantifying the qualitative attributes of the measurement objects. This paper proposes a Fuzzy Qualitative Evaluation System (FQES) using expert judgment to evaluate perceived qualitative attributes. FQES highlights the fusion of the capabilities of humans and computers in the qualitative evaluation process as humans are proficient in fuzzy reasoning and classification, while computers are superior in calculating human fuzzy inputs with embedded fuzzy algorithms derived in this paper. The innovative methods for the fusion of the capabilities includes a Fuzzy Compound Linguistic Variable (FCLV) for two dimensional rating categories, a Double Step Rating Approach for determination using FCLV, a Parabola-based Fuzzy Normal Distribution (FND) for assigning fuzzy numbers for the FCLV and a 5-layer Fuzzy Analytical Network (5FAN) which is the multi-granularity aggregation system taking multiple fuzzy number inputs to infer the result using an parametric function. FQES could be the ideal framework to increase the assessment accuracy for qualitative evaluation applications such as customer satisfaction surveys, employee satisfaction surveys, vendor surveys and risk assessment surveys. In the application, this paper demonstrates how FQES can be used to identify the optimum number for the selection of suppliers.
rating scale linguistic modeling fuzzy theory aggregation process decision analysis