Double hierarchy hesitant fuzzy linguistic entropy-based TODIM approach using evidential theory.

Double hierarchy hesitant fuzzy linguistic term sets (DHHFLTSs) can describe hesitation more accurately and reasonably than other linguistic representation models by adding a second hierarchy hesitant fuzzy linguistic term set. The Dempster–Shafer evidence theory (DSET) can minimize the loss of evaluation information in denoting and fusing uncertain information, and TODIM (an acronym in Portuguese for interactive and multi-criteria decision making) can consider the loss aversion behavior of decision makers (DMs). Considering their unique advantages, in this study, we propose a novel multiple criteria group decision-making method based on DSET and TODIM under the DHHFLTSs. First, we improve the cumulative functions and distance measure of DHHFLTSs. Next, we apply DSET to fuse double hierarchy hesitant fuzzy linguistic (DHHFL) information provided by a group of experts and obtain an evidence matrix consisting of belief degrees and DHHFLTSs. Then, we use the TODIM method to address the evidence matrix based on improved cumulative functions and distance measures to obtain the final ranking results. Finally, a weight determination model is constructed based on information entropy in the scenario of completely unknown weights. The newly proposed method reduces the loss of evaluation information and also considers the loss aversion behavior of DMs. Furthermore, an application example of a postgraduate course evaluation is used to demonstrate the effectiveness and rationality of the proposed method. Additionally, we compare the proposed method with other existing methods to further demonstrate the advantages of the proposed method. [ABSTRACT FROM AUTHOR]