Hesitant fuzzy linguistic term set (HFLTS) is a very useful technology in dealing with decision-making problems where people have hesitancy in providing their linguistic assessments. Distinct methods have been developed to aid decision making with HFLTSs, yet there is little research involving the issue that how to deal with the multigranularity hesitant fuzzy linguistic information. The aim of this paper is to develop the aggregation method for multigranularity hesitant fuzzy linguistic information and solve the linguistic group decision problem with different linguistic term sets. To do so, we first modify the translation functions and aggregation operators in the existing 2-tuple linguistic representation models so as to aggregate linguistic terms from different linguistic term sets. Then, we introduce the notion of hesitant 2-tuple sets to make computation of HFLTSs without loss of information, and develop some new operators to aggregate HFLTSs from different linguistic term sets. Using these operators, we propose a method to deal with multigranularity linguistic group decision-making problems with different situations where importance weights of either criteria or experts are known or unknown. Finally, the multigranularity linguistic group decision-making model is implemented to the healthcare waste treatment in West China Hospital to validate its effectiveness and efficiency in aiding decision-making process.

Ordered weighted averaging (OWA) operator's weights and orness measure play important roles in the application of the OWA operator to decision-making problems because the decision result may be different owing to the change in either of them. The aim of this paper is to investigate the influence that the change of OWA operator's weights or orness measure exerts on the decision result. We first give the range of the OWA operator's weights to keep the ranking order of alternatives or the optimal alternative unchanged. Then we make a sensitivity analysis to the orness measure to explore the dependency of the decision result on the orness measure. The results of analysis may provide a decision basis according to which decision makers are able to make a reasonable decision. Finally, a practical example is provided to illustrate the proposed sensitivity analysis methods.

This paper deals with multicriteria decision-making problems in which the criteria are partitioned into q categories, and a prioritization relationship exists over categories. We aggregate the criteria in the same priority category by a weighted OWA (ordered weighted averaging) operator and introduce two averaging operators, a generalized prioritized averaging operator and a generalized prioritized OWA operator. In the case with one criterion in each priority category, the two operators reduce to the prioritized averaging operator and the prioritized OWA operator as proposed by Yager. © 2012 Wiley Periodicals, Inc.