An Integrated Decision Framework for Group Decision-Making with Double Hierarchy Hesitant Fuzzy Linguistic Information and Unknown Weights

Abstract

As an attractive generalization to hesitant fuzzy linguistic term set, double hierarchy hesitant fuzzy linguistic term set (DHHFLTS) is used to represent complex linguistic expressions by providing rich and flexible context. Previous studies on DHHFLTS show that aggregation of preference information does not consider the interrelationship among attributes. Motivated by this challenge, in this paper, we extend the generalized Maclaurin symmetric mean (GMSM) operator to DHHFLTS. The GMSM operator is highly generalized and captures the interrelationship among attributes effectively. The attributes’ weight values are determined by using statistical variance method under DHHFLTS context. The decision makers’ weights are calculated by using newly proposed evidence theory-based Bayesian approximation method with double hierarchy preference information. A new extension to the Borda method is provided under DHHFLTS context for prioritizing objects. Also, the applicability of the proposed method is demonstrated by using a green supplier selection problem for a sports company. Finally, the superiorities and limitations of the proposed method are discussed in comparison with similar methods.