79 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
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
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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Some q-rung orthopair fuzzy Muirhead means with their application to multi-attribute group decision making
Recently proposed q-rung orthopair fuzzy set (q-ROFS) is a powerful and effective tool to describe fuzziness, uncertainty and vagueness. The prominent feature of q-ROFS is that the sum and square sum of membership and non-membership degrees are allowed to be greater than one with the sum of qth power of the membership degree and qth power of the non-membership degree is less than or equal to one. This characteristic makes q-ROFS more powerful and useful than intuitionistic fuzzy set (IFS) and Pythagorean fuzzy set (PFS). The aim of this paper is to develop some aggregation operators for fusing q-rung orthopair fuzzy information. As the Muirhead mean (MM) is considered as a useful aggregation technology which can capture interrelationships among all aggregated arguments, we extend the MM to q-rung orthopair fuzzy environment and propose a family of q-rung orthopair fuzzy Muirhead mean operators. Moreover, we investigate some desirable properties and special cases of the proposed operators. Further, we apply the proposed operators to solve multi-attribute group decision making (MAGDM) problems. Finally, a numerical instance as well as some comparative analysis are provided to demonstrate the validity and superiorities of the proposed method
CODAS method for 2-tuple linguistic Pythagorean fuzzy multiple attribute group decision making and its application to financial management performance assessment
Financial management performance evaluation (FMPE) has a significant effect on the identifying an investment chance. We can usually consider FMPE as a multiple attribute group decision making (MAGDM) issue, and the MAGDM method is needed to address it. Uncertainty may be one of the significant factors which could influence the process of MAGDM. In order to handle the uncertainty of group decision-making issues, MAGDM approaches along with 2-tuple linguistic Pythagorean fuzzy sets (2TLPFSs) have been designed. In this essay, CODAS method is extended to 2TLPFSs to tackle MAGDM issues. Linguistic variables and 2TLPFSs are also used to extend the CODAS method. An application of the presented 2-tuple linguistic Pythagorean fuzzy CODAS (2TLPF-CODAS) method to a case study of FMPE problem with 2-tuple linguistic Pythagorean fuzzy numbers (2TLPFNs) is given. To confirm the results, a comparative analysis between the fuzzy CODAS and 2TLPF-TODIM is performed. The results of the comparison illustrate that the presented 2TLPF-CODAS method offers effective and steady results
Pythagorean fuzzy Muirhead mean operators in multiple attribute decision making for evaluating of emerging technology commercialization
In today’s world, with the advancement of technology, several emerging technologies are coming. Faced with massive emerging technologies which are the component of the technology pool, how to identify the commercial potential of emerging technologies in theory and practice is an important problem. The scientific approach to the selection of these emerging technologies is one of the main objectives of the research. In this paper, we extend Muirhead mean (MM) operator and dual MM (DMM) operator to process the Pythagorean fuzzy numbers (PFNs) and then to solve the multiple attribute decision making (MADM) problems. Firstly, we develop some Pythagorean fuzzy Muirhead mean operators by extending MM and DMM operators to Pythagorean fuzzy information. Then, we prove some properties and discuss some special cases with respect to the parameter vector. Moreover, we present some new methods to deal with MADM problems with the PFNs based on the proposed MM and DMM operators. Finally, we verify the validity and reliability of our methods by using an application example for potential evaluation of emerging technology commercialization, and analyze the advantages of our methods by comparing with other existing method
Algorithms for probabilistic uncertain linguistic multiple attribute group decision making based on the GRA and CRITIC method: application to location planning of electric vehicle charging stations
Electric vehicles (EVs) could be regarded as one of the most
innovative and high technologies all over the world to cope with
the fossil fuel energy resource crisis and environmental pollution
issues. As the initiatory task of EV charging station (EVCS) construction,
site selection play an important part throughout the
whole life cycle, which is deemed to be multiple attribute group
decision making (MAGDM) problem involving many experts and
many conflicting attributes. In this paper, a grey relational analysis
(GRA) method is investigated to tackle the probabilistic uncertain
linguistic MAGDM in which the attribute weights are completely
unknown information. Firstly, the definition of the expected value
is then employed to objectively derive the attribute weights
based on the CRiteria Importance Through Intercriteria Correlation
(CRITIC) method. Then, the optimal alternative is chosen by calculating
largest relative relational degree from the probabilistic
uncertain linguistic positive ideal solution (PULPIS) which considers
both the largest grey relational coefficient from the PULPIS and the
smallest grey relational coefficient from the probabilistic uncertain
linguistic negative ideal solution (PULNIS). Finally, a numerical
case for site selection of electric vehicle charging stations (EVCS) is
designed to illustrate the proposed method. The result shows the
approach is simple, effective and easy to calculate
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