As a generalization of intuitionistic fuzzy set, the Pythagorean fuzzy set is interesting and very useful in modeling uncertain information in real-world decision-making problems. In this paper, we develop a new method for Pythagorean fuzzy multiple-criteria decision-making (MCDM) problems with aggregation operators and distance measures. First, we present the Pythagorean fuzzy ordered weighted averaging weighted average distance (PFOWAWAD) operator. The main advantage of the PFOWAWAD operator is that it uses distance measures in a unified framework between the ordered weighted averaging (OWA) operator and weighted average (WA) that considers the degree of importance of each concept in the aggregation. Some of its main properties and special cases are studied. Then, based on the proposed operator, a hybrid TOPSIS method, called PFOWAWAD-TOPSIS is introduced for Pythagorean fuzzy MCDM problem. Finally, a numerical example is provided to illustrate the practicality and feasibility of the developed method.

A Hybrid Method for Pythagorean Fuzzy Multiple-Criteria Decision Making

In many real-life decision making (DM) situations, the available information is vague or imprecise. To adequately solve decision problems with vague or imprecise information, fuzzy set theory and a...

Decision Making Methods Based on Fuzzy Aggregation Operators: Three Decades Review from 1986 to 2017

The aim of this paper is to put forward a consensus reaching method for multi-attribute group decision-making MAGDM problems with linguistic information, in which the weight information of experts and attributes is unknown. First, some basic concepts and operational laws of 2-tuple linguistic label are introduced. Then, a grey relational analysis method and a maximising deviation method are proposed to calculate the incomplete weight information of experts and attributes respectively. To eliminate the conflict in the group, a weight-updating model is employed to derive the weights of experts based on their contribution to the consensus reaching process. After conflict elimination, the final group preference can be obtained which will give the ranking of the alternatives. The model can effectively avoid information distortion which is occurred regularly in the linguistic information processing. Finally, an illustrative example is given to illustrate the application of the proposed method and comparative analysis with the existing methods are offered to show the advantages of the proposed method.

A consensus reaching model for 2-tuple linguistic multiple attribute group decision making with incomplete weight information

A new method for multiple criteria group decision making with incomplete weight information under linguistic environment

Multiple‐attribute group decision making (MAGDM) under linguistic environment is an important part of modern decision sciences, and information aggregation operator plays an import role in solving MAGDM problems. In this paper, an approach for solving MAGDM problem with q‐rung orthopair fuzzy 2‐tuple linguistic information is developed. First, the q‐rung orthopair fuzzy 2‐tuple linguistic weighted averaging (q‐ROFTLWA) operator and the q‐rung orthopair fuzzy 2‐tuple linguistic weighted geometric (q‐ROFTLWG) operator are presented. Furthermore, the q‐rung orthopair fuzzy 2‐tuple linguistic Muirhead mean (q‐ROFTLMM) operator and the q‐rung orthopair fuzzy 2‐tuple linguistic dual Muirhead mean (q‐ROFTLDMM) operator are proposed on the basis of Muirhead mean (MM) operator and dual Muirhead mean (DMM) operator. Then, an approach is developed to deal with MAGDM problem under q‐rung orthopair fuzzy 2‐tuple linguistic environment based on the proposed operators. Finally, a numerical example for selecting desirable emergency alternative(s) in the process of designing emergency preplan is given to illustrate the application of the developed method and demonstrate its effectiveness.

Shouzhen Zeng

Papers

A method based on induced aggregation operators and distance measures to multiple attribute decision making under 2-tuple linguistic environment