Method of multi-criteria group decision-making based on cloud aggregation operators with linguistic information

Abstract

The cloud model, which can synthetically describe the randomness and fuzziness of qualitative concepts and implement uncertain transformations between a qualitative concept and its quantitative instantiations, has attracted considerable attention from researchers studying multi-criteria group decision-making problems involving linguistic information. In this paper, some operations of clouds and several new aggregation operators are proposed. These include the cloud weighted arithmetic averaging (CWAA) operator, cloud-ordered weighted arithmetic averaging (COWA) operator, and cloud hybrid arithmetic (CHA) operator. The conversion between linguistic variables and clouds is introduced. Based on this conversion, a linguistic multi-criteria group decision-making method is developed. In this method, linguistic variables are first converted into clouds and then aggregated using cloud aggregation operators. The proposed method is then compared to the existing methods to confirm its feasibility and rationality.