No abstract

Cubic intuitionistic fuzzy (CIF) set is the hybrid set which can contain much more information to express an interval-valued intuitionistic fuzzy set and an intuitionistic fuzzy set simultaneously for handling the uncertainties in the data. Unfortunately, there has been no research on the aggregation operators on CIF sets so far. Since an aggregation operator is an important mathematical tool in decision-making problems, the present paper proposes some new Bonferroni mean and weighted Bonferroni mean averaging operators between the cubic intuitionistic fuzzy numbers for aggregating the different preferences of the decision-maker. Then, we develop a decision-making method based on the proposed operators under the cubic intuitionistic fuzzy environment and illustrated with a numerical example. Finally, a comparison analysis between the proposed and the existing approaches have been performed to illustrate the applicability and feasibility of the developed decision-making method.

Probabilistic dual hesitant fuzzy set (PDHFS) is an enhanced version of a dual hesitant fuzzy set (DHFS) in which each membership and non-membership hesitant value is considered along with its occurrence probability. These assigned probabilities give more details about the level of agreeness or disagreeness. By emphasizing the advantages of the PDHFS and the aggregation operators, in this manuscript, we have proposed several weighted and ordered weighted averaging and geometric aggregation operators by using Einstein norm operations, where the preferences related to each object is taken in terms of probabilistic dual hesitant fuzzy elements. Several desirable properties and relations are also investigated in details. Also, we have proposed two distance measures and its based maximum deviation method to compute the weight vector of the different criteria. Finally, a multi-criteria group decision-making approach is constructed based on proposed operators and the presented algorithm is explained with the help of the numerical example. The reliability of the presented decision-making method is explored with the help of testing criteria and by comparing the results of the example with several prevailing studies.

No abstract

The objective of this work is to present a novel Multi-Criteria Group Decision-Making (MCGDM) method under the Cubic Intuitionistic Fuzzy (CIF) environment by integrating it with the extended TOPSIS method. In the existing studies, uncertainties, which are present in the data, are handled with either Interval-Valued Intuitionistic Fuzzy Sets (IVIFS) or Intuitionistic Fuzzy Set (IFS) information, which may lose some useful information of alternatives. On the other hand, CIF Set (CIFS) handles the uncertainties by considering both the IVIFS and IFS simultaneously. Thus, motivated by this, in the present work, some series of distance measures between the pairs of CIFSs were presented, and their various relationships were investigated. Further, under this environment, a group decision-making method based on the proposed measure was presented by considering the di erent priority pairs of the decision-makers. A practical example was provided to verify the developed approach and, demonstrate its practicality and feasibility, their results were compared with those of the several existing approaches.

No abstract

No abstract

No abstract