Multi-attribute group decision making method with dual comprehensive clouds under information environment of dual uncertain Z-numbers

Abstract

Recognizing the subjectivity in human judgment and the limits to human cognition, fuzzy linguistic variables and uncertain linguistic variables are widely used to express the preference information of the decision experts in Multi-Attribute Group Decision Making (MAGDM). This paper develops an MAGDM method to solve a decision problem in which the attribute values are fuzzy numbers characterized by uncertain linguistic variables, that is, dual uncertain Z-numbers. The notion of the dual uncertain Z-number is first proposed based on the classical Z-number. Next, the cloud model is introduced, together with a new notion of the dual comprehensive cloud. A method of transforming the dual uncertain Z-numbers into dual comprehensive clouds is proposed. Third, a new dual comprehensive cloud-weighted averaging operator (DCC-WA) is presented to aggregate the multiple dual comprehensive clouds. Fourth, a new dual comprehensive cloud-grey relational degree (DCC-GRD) is supplied, and a novel MAGDM method based on the DCC-GRD is proposed. Finally, a group decision making case of sustainable supplier selection is provided to validate the proposed method. A sensitivity analysis and comparison with several congeneric methods are conducted.