scholarly journals Group decision making approach based on possibility degree measure under linguistic interval-valued intuitionistic fuzzy set environment

2020 ◽  
Vol 16 (1) ◽  
pp. 445-467 ◽  
Author(s):  
Harish Garg ◽  
◽  
Kamal Kumar
2015 ◽  
Vol 2015 ◽  
pp. 1-15 ◽  
Author(s):  
Wei Liang ◽  
Xiaolu Zhang ◽  
Manfeng Liu

As a new extension of Pythagorean fuzzy set (also called Atanassov’s intuitionistic fuzzy set of second type), interval-valued Pythagorean fuzzy set which is parallel to Atanassov’s interval-valued intuitionistic fuzzy set has recently been developed to model imprecise and ambiguous information in practical group decision making problems. The aim of this paper is to put forward a novel decision making method for handling multiple criteria group decision making problems within interval-valued Pythagorean fuzzy environment based on interval-valued Pythagorean fuzzy numbers (IVPFNs). There are three key issues being addressed in this approach. The first is to introduce an interval-valued Pythagorean fuzzy weighted arithmetic averaging (IVPF-WAA) operator to aggregate the decision data in order to get the overall preference values of alternatives. Some desirable properties of the IVPF-WAA operator are also investigated. Based on the idea of the maximizing deviation method, the second is to establish an optimization model for determining the weights of criteria for each expert. The third is to construct a minimizing consistency optimal model to derive the weights of criteria for the group. Finally, an illustrating example is given to verify the proposed approach.


Author(s):  
Sujit Das ◽  
Samarjit Kar ◽  
Tandra Pal

Abstract This article proposes an algorithmic approach for multiple attribute group decision making (MAGDM) problems using interval-valued intuitionistic fuzzy soft matrix (IVIFSM) and confident weight of experts. We propose a novel concept for assigning confident weights to the experts based on cardinals of interval-valued intuitionistic fuzzy soft sets (IVIFSSs). The confident weight is assigned to each of the experts based on their preferred attributes and opinions, which reduces the chances of biasness. Instead of using medical knowledgebase, the proposed algorithm mainly relies on the set of attributes preferred by the group of experts. To make the set of preferred attributes more important, we use combined choice matrix, which is combined with the individual IVIFSM to produce the corresponding product IVIFSM. This article uses IVIFSMs for representing the experts’ opinions. IVIFSM is the matrix representation of IVIFSS and IVIFSS is a natural combination of interval-valued intuitionistic fuzzy set (IVIFS) and soft set. Finally, the performance of the proposed algorithm is validated using a case study from real life


2021 ◽  
Vol 2021 ◽  
pp. 1-31
Author(s):  
Harish Garg ◽  
Zeeshan Ali ◽  
Jeonghwan Gwak ◽  
Tahir Mahmood ◽  
Sultan Aljahdali

In this paper, a new decision-making algorithm has been presented in the context of a complex intuitionistic uncertain linguistic set (CIULS) environment. CIULS integrates the concept the complex of a intuitionistic fuzzy set (CIFS) and uncertain linguistic set (ULS) to deal with uncertain and imprecise information in a more proactive manner. To investigate the interrelation between the pairs of CIULSs, we combine the concept of the Heronian mean (HM) and the complex intuitionistic uncertain linguistic (CIUL) to describe some new operators, namely, CIUL arithmetic HM (CIULAHM), CIUL weighted arithmetic HM (CIULWAHM), CIUL geometric HM (CIULGHM), and CIUL weighted geometric HM (CIULWGHM). The main advantage of these suggested operators is that they considered the interaction between pairs of objects during the formulation process. Also, a number of distinct brief cases and properties of the operators are analyzed. In addition, based on these operators, we have stated a MAGDM (“multiattribute group decision-making”) problem-solving algorithm. The consistency of the algorithm is illustrated by a computational example that compares the effects of the algorithm with a number of well-known existing methods.


2018 ◽  
Vol 14 (03) ◽  
pp. 343-361 ◽  
Author(s):  
K. Rahman ◽  
A. Ali ◽  
S. Abdullah ◽  
F. Amin

Interval-valued Pythagorean fuzzy set is one of the successful extensions of the interval-valued intuitionistic fuzzy set for handling the uncertainties in the data. Under this environment, in this paper, we introduce the notion of induced interval-valued Pythagorean fuzzy Einstein ordered weighted averaging (I-IVPFEOWA) aggregation operator. Some of its desirable properties namely, idempotency, boundedness, commutatively, monotonicity have also been proved. The main advantage of using the proposed operator is that this operator gives a more complete view of the problem to the decision-makers. The method proposed in this paper provides more general, more accurate and precise results as compared to the existing methods. Therefore this method play a vital role in real world problems. Finally, we apply the proposed operator to deal with multi-attribute group decision- making problems under interval-valued Pythagorean fuzzy information. The approach has been illustrated with a numerical example from the field of the decision-making problems to show the validity, practicality and effectiveness of the new approach.


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