235 research outputs found
Pythagorean 2-tuple linguistic power aggregation operators in multiple attribute decision making
In this paper, we investigate the multiple attribute decision making
problems with Pythagorean 2-tuple linguistic information.
Then, we utilize power average and power geometric operations
to develop some Pythagorean 2-tuple linguistic power aggregation
operators: Pythagorean 2-tuple linguistic power weighted
average (P2TLPWA) operator, Pythagorean 2-tuple linguistic power
weighted geometric (P2TLPWG) operator, Pythagorean 2-tuple linguistic
power ordered weighted average (P2TLPOWA) operator,
Pythagorean 2-tuple linguistic power ordered weighted geometric
(P2TLPOWG) operator, Pythagorean 2-tuple linguistic power
hybrid average (P2TLPHA) operator and Pythagorean 2-tuple linguistic
power hybrid geometric (P2TLPHG) operator. The prominent
characteristic of these proposed operators are studied. Then,
we have utilized these operators to develop some approaches to
solve the Pythagorean 2-tuple linguistic multiple attribute decision
making problems. Finally, a practical example for enterprise
resource planning (ERP) system selection is given to verify the
developed approach and to demonstrate its practicality and
effectiveness
Q-rung orthopair normal fuzzy aggregation operators and their application in multi-attribute decision-making
© 2019 by the authors. Q-rung orthopair fuzzy set (q-ROFS) is a powerful tool to describe uncertain information in the process of subjective decision-making, but not express vast objective phenomenons that obey normal distribution. For this situation, by combining the q-ROFS with the normal fuzzy number, we proposed a new concept of q-rung orthopair normal fuzzy (q-RONF) set. Firstly, we defined the conception, the operational laws, score function, and accuracy function of q-RONF set. Secondly, we presented some new aggregation operators to aggregate the q-RONF information, including the q-RONF weighted operators, the q-RONF ordered weighted operators, the q-RONF hybrid operator, and the generalized form of these operators. Furthermore, we discussed some desirable properties of the above operators, such as monotonicity, commutativity, and idempotency. Meanwhile, we applied the proposed operators to the multi-attribute decision-making (MADM) problem and established a novel MADM method. Finally, the proposed MADM method was applied in a numerical example on enterprise partner selection, the numerical result showed the proposed method can effectively handle the objective phenomena with obeying normal distribution and complicated fuzzy information, and has high practicality. The results of comparative and sensitive analysis indicated that our proposed method based on q-RONF aggregation operators over existing methods have stronger information aggregation ability, and are more suitable and flexible for MADM problems
VIKOR method for multiple criteria group decision making under 2-tuple linguistic neutrosophic environment
In this article, the VIKOR method is proposed to solve the multiple
criteria group decision making (MCGDM) with 2-tuple linguistic
neutrosophic numbers (2TLNNs). Firstly, the fundamental concepts,
operation formulas and distance calculating method of
2TLNNs are introduced. Then some aggregation operators of
2TLNNs are reviewed. Thereafter, the original VIKOR method is
extended to 2TLNNs and the calculating steps of VIKOR method
with 2TLNNs are proposed. In the proposed method, it’s more
reasonable and scientific for considering the conflicting criteria.
Furthermore, the VIKOR are extended to interval-valued 2-tuple
linguistic neutrosophic numbers (IV2TLNNs). Moreover, a numerical
example for green supplier selection has been given to illustrate
the new method and some comparisons are also conducted
to further illustrate advantages of the new method
Pythagorean fuzzy combinative distance-based assessment with pure linguistic information and its application to financial strategies of multi-national companies
This article addresses the issue of selecting Financial Strategies in
Multi-National companies (F.S.M.). The F.S.M. typically has to consider
multiple factors involving multiple stakeholders and, hence,
can be handled by applying an appropriate Multi-Criteria Group
Decision-Making (M.C.G.D.M.) approach. To address this issue, we
develop an M.C.G.D.M. framework to tackle the F.S.M. problem. To
handle inherent uncertainty in business decisions as reflected by
linguistic reasoning, we embark on constructing a Linguistic
Pythagorean Fuzzy (L.P.F.) M.C.G.D.M. framework that is capable
of tackling both uncertain decision information and linguistic variables.
The proposed approach extends the combinative distancebased
assessment (C.O.D.A.S.) method into the L.P.F. environment,
and processes decision input expressed as Pythagorean fuzzy sets
(P.F.S.) and pure linguistic variables (rather than converting linguistic
information into fuzzy numbers). The developed L.P.F.-
C.O.D.A.S. technique aggregates the L.P.F. information and is
applied to the F.S.M. problem with uncertain linguistic information.
A comparative analysis is carried out to compare the results
obtained from the proposed L.P.F.-C.O.D.A.S. approach with those
from other extensions of C.O.D.A.S. Furthermore, a sensitivity analysis
is conducted to check the impact of changes in a distance
threshold parameter on the ranking results
An Extended VIKOR Method for Multiple Criteria Group Decision Making with Triangular Fuzzy Neutrosophic Numbers
In this article, we combine the original VIKOR model with a triangular fuzzy neutrosophic set to propose the triangular fuzzy neutrosophic VIKOR method. In the extended method, we use the triangular fuzzy neutrosophic numbers (TFNNs) to present the criteria values in multiple criteria group decision making (MCGDM) problems. Firstly, we summarily introduce the fundamental concepts, operation formulas and distance calculating method of TFNNs. Then we review some aggregation operators of TFNNs. Thereafter, we extend the original VIKOR model to the triangular fuzzy neutrosophic environment and introduce the calculating steps of the TFNNs VIKOR method, our proposed method which is more reasonable and scientific for considering the conflicting criteria. Furthermore, a numerical example for potential evaluation of emerging technology commercialization is presented to illustrate the new method, and some comparisons are also conducted to further illustrate advantages of the new method
The generalized dice similarity measures for multiple attribute decision making with hesitant fuzzy linguistic information
In this paper, we shall present some novel Dice similarity measures of hesitant fuzzy linguistic term sets and the generalized Dice similarity measures of hesitant fuzzy linguistic term sets and indicate that the Dice similarity measures and asymmetric measures (projection measures) are the special cases of the generalized Dice similarity measures in some parameter values. Then, we propose the generalized Dice similarity measures-based multiple attribute decision making models with hesitant fuzzy linguistic term sets. Finally, a practical example concerning the evaluation of the quality of movies is given to illustrate the applicability and advantage of the proposed generalized Dice similarity measure
The generalized dice similarity measures for multiple attribute decision making with hesitant fuzzy linguistic information
In this paper, we shall present some novel Dice similarity measures of hesitant fuzzy linguistic term sets and the generalized Dice similarity measures of hesitant fuzzy linguistic term sets and indicate that the Dice similarity measures and asymmetric measures (projection measures) are the special cases of the generalized Dice similarity measures in some parameter values. Then, we propose the generalized Dice similarity measures-based multiple attribute decision making models with hesitant fuzzy linguistic term sets. Finally, a practical example concerning the evaluation of the quality of movies is given to illustrate the applicability and advantage of the proposed generalized Dice similarity measure
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