ABSTRACT
Practical group decision-making (DM) problems frequently involve challenging circumstances when attempting to assign appropriate values to the data because of the haziness and uncertainty of the surrounding circumstances. In order to address the ambiguity and imprecision that arise in DM issues, q-rung picture fuzzy sets (q-RPFSs) have a more broader structure. In this research, the criteria importance through intercriteria correlation (CRITIC) and the decision-making trial and evaluation laboratory (DEMATEL) techniques are separately integrated with the multi-attributive border approximation area comparison (MABAC) method. The MABAC method, which measures how far each alternative is from the border approximation area, is very stable and useful for resolving real-world problems. The CRITIC technique calculates the criteria weights by taking into account the relationships between attributes, and the DEMATEL methodology is recognized as the best method for determining how several criteria or factors interact with one another. As a result of these justifications, we made the decision to create the CRITIC-MABAC and DEMATEL-MABAC procedures for q-RPFSs. By using the suggested strategies, the primary goal of this article is to determine the occupational risk that has the greatest impact on the health of a hospital's medical staff. We begin by employing the CRITIC technique to determine the criteria weights. In addition, we calculate the weights of the criteria using the DEMATEL approach. The offered methodologies are investigated for their applicability to determine the most serious occupational hazard for hospital employees. We conducted a comparison with three earlier studies to verify the accuracy of the tactics that are offered.
ABSTRACT
In this article, we introduce dual hesitant q -rung orthopair fuzzy 2-tuple linguistic set (DHq-ROFTLS), a new strategy for dealing with uncertainty that incorporates a 2-tuple linguistic term into dual hesitant q -rung orthopair fuzzy set (DHq-ROFS). DHq-ROFTLS is a better way to deal with uncertain and imprecise information in the decision-making environment. We elaborate the operational rules, based on which, the DHq-ROFTL weighted averaging (DHq-ROFTLWA) operator and the DHq-ROFTL weighted geometric (DHq-ROFTLWG) operator are presented to fuse the DHq-ROFTL numbers (DHq-ROFTLNs). As Maclaurin symmetric mean (MSM) aggregation operator is a useful tool to model the interrelationship between multi-input arguments, we generalize the traditional MSM to aggregate DHq-ROFTL information. Firstly, the DHq-ROFTL Maclaurin symmetric mean (DHq-ROFTLMSM) and the DHq-ROFTL weighted Maclaurin symmetric mean (DHq-ROFTLWMSM) operators are proposed along with some of their desirable properties and some special cases. Further, the DHq-ROFTL dual Maclaurin symmetric mean (DHq-ROFTLDMSM) and weighted dual Maclaurin symmetric mean (DHq-ROFTLWDMSM) operators with some properties and cases are presented. Moreover, the assessment and prioritizing of the most important aspects in multiple attribute group decision-making (MAGDM) problems is analysed by an extended novel approach based on the proposed aggregation operators under DHq-ROFTL framework. At long last, a numerical model is provided for the selection of adequate medication to control COVID-19 outbreaks to demonstrate the use of the generated technique and exhibit its adequacy. Finally, to analyse the advantages of the proposed method, a comparison analysis is conducted and the superiorities are illustrated.
