Fuzzy multi-attribute group decision making method with incomplete weight information under interval type-2 fuzzy environment

Abstract

Interval type-2 fuzzy sets (IT2 FS) can provide us with more degrees of freedom to represent the uncertainty and the vagueness of the real world. In this paper, we investigate the fuzzy multi-attribute group decision making (FMAGDM) problems in which all the information provided by the decision makers (DMs) is expressed as IT2 FS, and the information about attribute weights is incomplete. We introduce the concepts of crisp possibility mean value and present a new method for calculating the possibility degree of two IT2 FS based on the interval-valued possibility mean values. Then, we propose a new method named maximizing deviations method for determine attribute weights information under interval type-2 fuzzy environment. Furthermore, we utilize the obtained attribute weights and the fuzzy possibility degree to fuse the IT2 fuzzy information in the collective IT2 fuzzy decision matrix to get the ranking values of all alternatives. A numerical example is given to illustrate the feasibility and effectiveness of the proposed method.