Consistent fuzzy preference relation with geometric Bonferroni mean: a fused preference method for assessing the quality of life

Fuzzy preference relation (FPR) is commonly used in solving multi-criteria decision making problems because of its efficiency in representing people’s perceptions. However, the FPR suffers from an intrinsic limitation of consistency in decision making. In this regard, many researchers proposed the consistent fuzzy preference relation (CFPR) as a decision-making approach. Nevertheless, most CFPR methods involve a traditional aggregation process which does not identify the interrelationship between the criteria of decision problems. In addition, the information provided by individual experts is indeed related to that provided by other experts. Therefore, the interrelationship of information on criteria should be dealt with. Based on this motivation, we propose a modified approach of CFPR with Geometric Bonferroni Mean (GBM) operator. The proposed method introduces the GBM as an operator to aggregate information. The proposed method is applied to a case study of assessing the quality of life among the population in Setiu Wetlands. It is shown that the best option derived by the proposed method is consistent with that obtained from the other methods, despite the difference in aggregation operators.