Pythagorean fuzzy multiattribute group decision making based on risk attitude and evidential reasoning methodology

Abstract

Two aspects of problems including selection of aggregation operator for extreme fuzzy evaluation value and risk attitude of decision makers cannot be well solved in Pythagorean fuzzy (PF) multiattribute group decision making (MAGDM). This paper extends the evidential reasoning aggregation method in the intuitionistic fuzzy environment, expands the dictionary ranking method by constructing interval‐valued numbers through the proposed credibility functions of PF values and the concept of closeness degree, widens the continuous generalized ordered weighted average ( normalC ‐ GOWA ) operator to establish a risk attitude ranking measure, and puts forward a PF MAGDM approach based on risk attitude and evidence reasoning methodology (ERM). First, the proposed method utilizes the ERM to aggregate each decision maker's decision matrix and the weights of the attributes to get his/her aggregated decision matrix. Then, it incorporates the obtained aggregated decision matrices of the experts, the weights of the experts and the ERM to accomplish the aggregated PF value of each alternative. Finally, the ranking measure value of risk attitude on each alternative's PF value is calculated, and the sensitivity analysis on the ranking measure function is carried out. The proposed method has overcome the drawbacks of the existing methods for fuzzy MAGDM in PF environments.

Classical dynamic consensus and opinion dynamics models: A survey of recent trends and methodologies

“…To quantify the attitude of DMs in a continuous ranging scale to reflect the pessimistic attitudes to indifferent attitudes in construction of the trust relationships, the authors in[94] proposed an attitudinal trust degree, which makes use of an ordered weighted average operator guided by a unit-monotonic function. Considering the risk attitude of DMs in alternative ranking through an evidential reasoning methodology[95] and construction of linguistic quantifiers based upon the attitude of DMs[96] are of recent trends in the design of attitude-based feedback mechanisms.As the last category of behavioral mechanisms, we review some recent advances on managing the non-cooperative behavior of DMs towards consensus reaching by means of a feedback mechanism. The non-cooperative behavior refers to the case, in which the inconsistent DMs are reluctant to modify their opinions according to the provided recommendations through the feedback mechanism.…”