Creating a common priority vector in intuitionistic fuzzy AHP: a comparison of entropy-based and distance-based models

Abstract In the case of conflicting individuals or evaluator groups, finding common preferences participants is a challenging task. This statement also refers to Intuitionistic Fuzzy Analytic Hierarchy Process models, in which uncertainty scoring well-handled, however, aggregation modified scores generally conducted by conventional way multi-criteria decision-making. paper offers two options for this aggregation: relatively well-known entropy-based, and lately emerged distance-based aggregations. The manuscript can be considered as pioneer work analyzing nature under fuzzy environment. proposed model, three clearly separable groups are examined, objective find their priority vector, satisfactory all participant clusters. We have tested model results on real-world study, public transport development decision-making problem conducting large-scale survey involving different stakeholder transportation. comparison approaches has shown that both entropy-based techniques provide feasible solution based high similarity final ordinal cardinal outcomes.