Статті в журналах: "2-TUPLE LINGUISTIC"

1

Singh, Anjali, and Anjana Gupta. "Some Observations on 2-tuple Linguistic and Interval 2-tuple Linguistic Operators." International Journal of Mathematical, Engineering and Management Sciences 4, no. 2 (April 1, 2019): 327–36. http://dx.doi.org/10.33889/ijmems.2019.4.2-026.

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Анотація:

Literature of aggregation operators defined in the domains of linguistic and interval-valued linguistic information is extensive and vast. But, some operators are not well-defined and do not benefit the researchers. In this paper, we have highlighted the flaws in defining the operators and demonstrated them via examples. Further, some remedial suggestions for the improvement of the definitions are given.

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2

Wei, Guiwu. "Model for Multiple Attribute Decision Making Based on Picture 2-Tuple Linguistic Power Aggregation Operators." International Journal of Decision Support System Technology 11, no. 1 (January 2019): 35–65. http://dx.doi.org/10.4018/ijdsst.2019010103.

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In this article, the authors investigate the multiple attribute decision making problems with picture 2-tuple linguistic information. The utilized power average and power geometric operations used to develop some picture 2-tuple linguistic power aggregation operators: picture 2-tuple linguistic power weighted average (P2TLPWA) operator, picture 2-tuple linguistic power weighted geometric (P2TLPWG) operator, picture 2-tuple linguistic power ordered weighted average (P2TLPOWA) operator, picture 2-tuple linguistic power ordered weighted geometric (P2TLPOWG) operator, picture 2-tuple linguistic power hybrid average (P2TLPHA) operator and picture 2-tuple linguistic power hybrid geometric (P2TLPHG) operator. The prominent characteristic of these proposed operators is studied. This article has utilized these operators to develop some approaches to solve the picture 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.

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3

Abdullah, Saleem, Omar Barukab, Muhammad Qiyas, Muhammad Arif, and Sher Afzal Khan. "Analysis of Decision Support System Based on 2-Tuple Spherical Fuzzy Linguistic Aggregation Information." Applied Sciences 10, no. 1 (December 30, 2019): 276. http://dx.doi.org/10.3390/app10010276.

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Анотація:

The aim of this paper is to propose the 2-tuple spherical fuzzy linguistic aggregation operators and a decision-making approach to deal with uncertainties in the form of 2-tuple spherical fuzzy linguistic sets. 2-tuple spherical fuzzy linguistic operators have more flexibility than general fuzzy set. We proposed a numbers of aggregation operators, namely 2-tuple spherical fuzzy linguistic weighted average, 2-tuple spherical fuzzy linguistic ordered weighted average, 2-tuple spherical fuzzy linguistic hybrid average, 2-tuple spherical fuzzy linguistic weighted geometric, 2-tuple spherical fuzzy linguistic ordered geometric, and 2-tuple spherical fuzzy linguistic hybrid geometric operators. The distinguishing feature of these proposed operators is studied. At that point, we have used these operators to design a model to deal with multiple attribute decision-making issues under the 2-tuple spherical fuzzy linguistic information. Then, a practical application for best company selection for feeds is given to prove the introduced technique and to show its practicability and effectiveness. Besides this, a systematic comparison analysis with other existent methods is conducted to reveal the advantage of our method. Results indicate that the proposed method is suitable and effective for decision making problems.

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4

Liu, Xi, Zhifu Tao, Huayou Chen, and Ligang Zhou. "A MAGDM Method Based on 2-Tuple Linguistic Heronian Mean and New Operational Laws." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 24, no. 04 (August 2016): 593–627. http://dx.doi.org/10.1142/s0218488516500288.

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Анотація:

In this paper, we investigate the multiple attributes group decision making (MAGDM) problem with 2-tuple linguistic information. According to some closed operational laws of 2-tuple linguistic, some Algebra t-norm and s-norm based Heronian aggregation operators of 2-tuple linguistic information are put forward, the desired properties and the special cases where the parameters take different values are also discussed. Furthermore, a method of MAGDM under 2-tuple linguistic environment is proposed based on the Algebra t-norm and s-norm based 2-tuple linguistic Heronian mean operator or the Algebra t-norm and s-norm based 2-tuple linguistic weighted Heronian mean operator. Finally, a numerical example is presented to demonstrate the proposed method.

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5

Shan, Meng-Meng, Jian-Xin You, and Hu-Chen Liu. "Some Interval 2-Tuple Linguistic Harmonic Mean Operators and Their Application in Material Selection." Advances in Materials Science and Engineering 2016 (2016): 1–13. http://dx.doi.org/10.1155/2016/7034938.

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We investigate the multiple attribute group material selection problems in which the attribute values take the form of interval 2-tuple linguistic information. Firstly, some operational laws and possibility degree of interval 2-tuple linguistic variables are introduced. Then, we develop some interval 2-tuple linguistic aggregation operators called interval 2-tuple hybrid harmonic mean (ITHHM) operator, induced interval 2-tuple ordered weighted harmonic mean (I-ITOWHM) operator, and induced interval 2-tuple hybrid harmonic mean (I-ITHHM) operator and study some desirable properties of the I-ITOWHM operator. In particular, all these operators can be reduced to aggregate 2-tuple linguistic variables. Based on the I-ITHHM and the ITWHM (interval 2-tuple weighted harmonic mean) operators, an approach to multiple attribute group decision-making with interval 2-tuple linguistic information is proposed. Finally, a practical application to material selection problem is given to verify the developed approach and to demonstrate its practicality and effectiveness.

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6

Zuo, Yuting, and Chunfang Chen. "A New Fuzzy Multiple Attribute Decision Making Method Based on the Utility Transformation Functions." Symmetry 11, no. 3 (March 21, 2019): 418. http://dx.doi.org/10.3390/sym11030418.

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Анотація:

The 2-tuple linguistic information model (2TLIM) is a useful tool to avoid the loss of information, which has been widely adapted in the study of the multiple attribute decision making (MADM) problem. However, there is a limitation, the limitation is that the difference between the neighboring 2-tuple linguistic information is fixed regardless of the decision-makers’ attitude. In this paper, we define the utility transformation functions based on the 2-tuple linguistic utility to overcome the drawback. Firstly, by introducing the economic utility theory, the 2-tuple linguistic utility is defined, the 2-tuple linguistic utility parameter (2TLUP) and the 2-tuple linguistic marginal utility (2TLMU) are constructed to achieve the measurement of the decision-makers’ attitude. The utility transformation functions are developed on the decision-makers’ attitude. Secondly, the 2-tuple linguistic operational laws are presented with the extended Hamacher T-norm (TN) and T-conorm (TC). Subsequently, we propose the 2-tuple linguistic utility weighted average (2TLUWA) operator and the method of MADM. Lastly, the application and the comparison with the existing methods are summarized to verify the practicality and advantages of the proposed method of MADM.

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7

Wang, Jie, Jianping Lu, Guiwu Wei, Rui Lin, and Cun Wei. "Models for MADM with Single-Valued Neutrosophic 2-Tuple Linguistic Muirhead Mean Operators." Mathematics 7, no. 5 (May 17, 2019): 442. http://dx.doi.org/10.3390/math7050442.

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In this article, we expand the Muirhead mean (MM) operator and dual Muirhead mean (DMM) operator with single-valued neutrosophic 2-tuple linguistic numbers (SVN2TLNs) to propose the single-valued neutrosophic 2-tuple linguistic Muirhead mean (SVN2TLMM) operator, the single-valued neutrosophic 2-tuple linguistic weighted Muirhead mean (SVN2TLWMM) operator, the single-valued neutrosophic 2-tuple linguistic dual Muirhead mean (SVN2TLDMM) operator, and the single-valued neutrosophic 2-tuple linguistic weighted dual Muirhead mean (SVN2TLWDMM) operator. Multiple attribute decision making (MADM) methods are then proposed using these operators. Finally, we utilize an applicable example for green supplier selection in green supply chain management to prove the proposed methods.

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8

Wang, Jie, Guiwu Wei, and Hui Gao. "Approaches to Multiple Attribute Decision Making with Interval-Valued 2-Tuple Linguistic Pythagorean Fuzzy Information." Mathematics 6, no. 10 (October 13, 2018): 201. http://dx.doi.org/10.3390/math6100201.

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The Maclaurin symmetric mean (MSM) operator is a classical mean type aggregation operator used in modern information fusion theory, which is suitable to aggregate numerical values. The prominent characteristic of the MSM operator is that it can capture the interrelationship among multi-input arguments. Motivated by the ideal characteristic of the MSM operator, in this paper, we expand the MSM operator, generalized MSM (GMSM), and dual MSM (DMSM) operator with interval-valued 2-tuple linguistic Pythagorean fuzzy numbers (IV2TLPFNs) to propose the interval-valued 2-tuple linguistic Pythagorean fuzzy MSM (IV2TLPFMSM) operator, interval-valued 2-tuple linguistic Pythagorean fuzzy weighted MSM (IV2TLPFWMSM) operator, interval-valued 2-tuple linguistic Pythagorean fuzzy GMSM (IN2TLPFGMSM) operator, interval-valued 2-tuple linguistic Pythagorean fuzzy weighted GMSM (IV2TLPFWGMSM) operator, interval-valued 2-tuple linguistic Pythagorean fuzzy DMSM (IN2TLPFDMSM) operator, Interval-valued 2-tuple linguistic Pythagorean fuzzy weighted DMSM (IV2TLPFWDMSM) operator. Then the multiple attribute decision making (MADM) methods are developed with these three operators. Finally, an example of green supplier selection is used to show the proposed methods.

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9

Deng, Xiumei, Jie Wang, Guiwu Wei, and Mao Lu. "Models for Multiple Attribute Decision Making with Some 2-Tuple Linguistic Pythagorean Fuzzy Hamy Mean Operators." Mathematics 6, no. 11 (October 31, 2018): 236. http://dx.doi.org/10.3390/math6110236.

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The Hamy mean (HM) operator, as a useful aggregation tool, can capture the correlation between multiple integration parameters, and the 2-tuple linguistic Pythagorean fuzzy numbers (2TLPFNs) are a special kind of Pythagorean fuzzy numbers (PFNs), which can easily describe the fuzziness in actual decision making by 2-tuple linguistic terms (2TLTs). In this paper, to consider both Hamy mean (HM) operator and 2TLPFNs, we combine the HM operator, weighted HM (WHM) operator, dual HM (DHM) operator, and dual WHM (DWHM) operator with 2TLPFNs to propose the 2-tuple linguistic Pythagorean fuzzy HM (2TLPFHM) operator, 2-tuple linguistic Pythagorean fuzzy WHM (2TLPFWHM) operator, 2-tuple linguistic Pythagorean fuzzy DHM (2TLPFDHM) operator and 2-tuple linguistic Pythagorean fuzzy DWHM (2TLPFDWHM) operator. Then some multiple attribute decision making (MADM) procedures are developed based on these operators. At last, an applicable example for green supplier selection is given.

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10

Naz, Sumera, Muhammad Akram, Mohammed M. Ali Al-Shamiri, Mohammed M. Khalaf, and Gohar Yousaf. "A new MAGDM method with 2-tuple linguistic bipolar fuzzy Heronian mean operators." Mathematical Biosciences and Engineering 19, no. 4 (2022): 3843–78. http://dx.doi.org/10.3934/mbe.2022177.

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<abstract>In this article, we introduce the 2-tuple linguistic bipolar fuzzy set (2TLBFS), a new strategy for dealing with uncertainty that incorporates a 2-tuple linguistic term into bipolar fuzzy set. The 2TLBFS 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 2-tuple linguistic bipolar fuzzy weighted averaging (2TLBFWA) operator and the 2-tuple linguistic bipolar fuzzy weighted geometric (2TLBFWG) operator are presented to fuse the 2TLBF numbers (2TLBFNs). The Heronian mean (HM) operator, which can reflect the internal correlation between attributes and their influence on decision results, is integrated into the 2TLBF environment to analyze the effect of the correlation between decision factors on decision results. Initially, the generalized 2-tuple linguistic bipolar fuzzy Heronian mean (G2TLBFHM) operator and generalized 2-tuple linguistic bipolar fuzzy weighted Heronian mean (G2TLBFWHM) operator are proposed and properties are explained. Further, 2-tuple linguistic bipolar fuzzy geometric Heronian mean (2TLBFGHM) operator and 2-tuple linguistic bipolar weighted geometric Heronian mean (2TLBFWGHM) operator are proposed along with some of their desirable properties. Then, an approach to multi-attribute group decision-making (MAGDM) based on the proposed aggregation operators under the 2TLBF framework is developed. At last, a numerical illustration is provided for the selection of the best photovoltaic cell to demonstrate the use of the generated technique and exhibit its adequacy.</abstract>

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11

WEI, G. W. "SOME HARMONIC AGGREGATION OPERATORS WITH 2-TUPLE LINGUISTIC ASSESSMENT INFORMATION AND THEIR APPLICATION TO MULTIPLE ATTRIBUTE GROUP DECISION MAKING." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 19, no. 06 (December 2011): 977–98. http://dx.doi.org/10.1142/s0218488511007428.

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With respect to multiple attribute group decision making problems with linguistic information of attribute values, a group decision analysis is proposed. Some new aggregation operators are proposed: the 2-tuple linguistic weighted harmonic averaging (TWHA), 2-tuple linguistic ordered weighted harmonic averaging (TOWHA) and 2-tuple linguistic combined weighted harmonic averaging (TCWHA) operator and properties of the operators are analyzed. Then, a method based on the TWHA and TCWHA operators for multiple attribute group decision making is presented. In this approach, alternative appraisal values are calculated by the aggregation of 2-tuple linguistic information. Thus, the ranking of alternative or selection of the most desirable alternative(s) is obtained by the comparison of 2-tuple linguistic information. Finally, a numerical example is used to illustrate the applicability and effectiveness of the proposed method.

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12

Rao, Congjun, Mark Goh, and Junjun Zheng. "Decision Mechanism for Supplier Selection Under Sustainability." International Journal of Information Technology & Decision Making 16, no. 01 (January 2017): 87–115. http://dx.doi.org/10.1142/s0219622016500450.

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Against the backdrop of responsible economic development, sustainable supply chain management (SSCM) is key to achieving the sustainable development for enterprise and industry. In this regard, sustainable supplier selection is crucial in SSCM. By integrating the three dimensions of sustainability, economic, environmental and social, this paper presents a new evaluation system for supplier selection from a sustainability perspective. Specifically, we design a decision mechanism for sustainable supplier selection based on linguistic 2-tuple grey correlation degree. In this proposed mechanism, the hybrid attribute values whereby real numbers, interval numbers and linguistic fuzzy variables coexist are transformed into linguistic 2-tuples. A ranking method based on linguistic 2-tuple grey correlation degree is then presented to rank the suppliers. An application example is presented to highlight the implementation, availability and feasibility of the proposed decision making mechanism.

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13

PEI, ZHENG, LI ZOU, and LIANGZHONG YI. "A LINGUISTIC AGGREGATION OPERATOR INCLUDING WEIGHTS FOR LINGUISTIC VALUES AND EXPERTS IN GROUP DECISION MAKING." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 21, no. 06 (December 2013): 927–43. http://dx.doi.org/10.1142/s0218488513500426.

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Different linguistic aggregation methods have been proposed and applied in the linguistic decision making problems. Generally, weights for experts or criteria are considered in linguistic aggregation processes. In this paper, we provide a method to discovery new forms to compute weights and new interpretations in the linguistic ordered weighted averaging operator. In linguistic decision analysis, it can be noticed that some of initial linguistic values used by experts have priority over others linguistic values in evaluation processes. We formalize the priority over initial linguistic values as weights for linguistic values, by considering weights for linguistic values as well as weights for experts, we provide an alternative method to discovery weights information of the linguistic ordered weighted averaging operator, its properties show that such linguistic aggregation operator is extensions of the 2-tuple arithmetic mean, the 2-tuple weighted aggregation operator and the 2-tuple ordered weighted averaging operator. By an illustrative example, we compare the linguistic aggregation operator with the 2-tuple weighted aggregation operator and the 2-tuple ordered weighted averaging operator in a decision making problem. From the practical point of view, we provide an optimization model to obtain such weights information in linguistic aggregation processes, examples show the linguistic aggregation operator as an alternative linguistic ordered weighted averaging operator in practice.

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14

Shan, Meng-Meng, Ping Li, and Hu-Chen Liu. "Interval 2-Tuple Linguistic Distance Operators and Their Applications to Supplier Evaluation and Selection." Mathematical Problems in Engineering 2016 (2016): 1–12. http://dx.doi.org/10.1155/2016/9893214.

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With respect to multicriteria supplier selection problems with interval 2-tuple linguistic information, a new decision making approach that uses distance measures is proposed. Motivated by the ordered weighted distance (OWD) measures, in this paper, we develop some interval 2-tuple linguistic distance operators such as the interval 2-tuple weighted distance (ITWD), the interval 2-tuple ordered weighted distance (ITOWD), and the interval 2-tuple hybrid weighted distance (ITHWD) operators. These aggregation operators are very useful for the treatment of input data in the form of interval 2-tuple linguistic variables. We study some desirable properties of the ITOWD operator and further generalize it by using the generalized and the quasi-arithmetic means. Finally, the new approach is utilized to complete a supplier selection study for an actual hospital from the healthcare industry.

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15

Faizi, Shahzad, Wojciech Sałabun, Nisbha Shaheen, Atiq ur Rehman, and Jarosław Wątróbski. "A Novel Multi-Criteria Group Decision-Making Approach Based on Bonferroni and Heronian Mean Operators under Hesitant 2-Tuple Linguistic Environment." Mathematics 9, no. 13 (June 24, 2021): 1489. http://dx.doi.org/10.3390/math9131489.

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Ambiguous and uncertain facts can be handled using a hesitant 2-tuple linguistic set (H2TLS), an important expansion of the 2-tuple linguistic set. The vagueness and uncertainty of data can be grabbed by using aggregation operators. Therefore, aggregation operators play an important role in computational processes to merge the information provided by decision makers (DMs). Furthermore, the aggregation operator is a potential mechanism for merging multisource data which is synonymous with cooperative preference. The aggregation operators need to be studied and analyzed from various perspectives to represent complex choice situations more readily and capture the diverse experiences of DMs. In this manuscript, we propose some valuable operational laws for H2TLS. These new operational laws work through the individual aggregation of linguistic words and the collection of translation parameters. We introduced a hesitant 2-tuple linguistic weighted average (H2TLWA) operator to solve multi-criteria group decision-making (MCGDM) problems. We also define hesitant 2-tuple linguistic Bonferroni mean (H2TLBM) operator, hesitant 2-tuple linguistic geometric Bonferroni mean (H2TLGBM) operator, hesitant 2-tuple linguistic Heronian mean (H2TLHM) operator, and a hesitant 2-tuple linguistic geometric Heronian mean (H2TLGHM) operator based on the novel operational laws proposed in this paper. We define the aggregation operators for addition, subtraction, multiplication, division, scalar multiplication, power and complement with their respective properties. An application example and comparison analysis were examined to show the usefulness and practicality of the work.

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16

Qin, Jindong, and Xinwang Liu. "2-tuple linguistic Muirhead mean operators for multiple attribute group decision making and its application to supplier selection." Kybernetes 45, no. 1 (January 11, 2016): 2–29. http://dx.doi.org/10.1108/k-11-2014-0271.

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Анотація:

Purpose – The purpose of this paper is to develop some 2-tuple linguistic aggregation operators based on Muirhead mean (MM), which is combined with multiple attribute group decision making (MAGDM) and applied the proposed MAGDM model for supplier selection under 2-tuple linguistic environment. Design/methodology/approach – The supplier selection problem can be regarded as a typical MAGDM problem, in which the decision information should be aggregated. In this paper, the authors investigate the MAGDM problems with 2-tuple linguistic information based on traditional MM operator. The MM operator is a well-known mean type aggregation operator, which has some particular advantages for aggregating multi-dimension arguments. The prominent characteristic of the MM operator is that it can capture the whole interrelationship among the multi-input arguments. Motivated by this idea, in this paper, the authors develop the 2-tuple linguistic Muirhead mean (2TLMM) operator and the 2-tuple linguistic dual Muirhead mean (2TLDMM) operator for aggregating the 2-tuple linguistic information, respectively. Some desirable properties and special cases are discussed in detail. Based on which, two approaches to deal with MAGDM problems under 2-tuple linguistic information environment are developed. Finally, a numerical example concerns the supplier selection problem is provided to illustrate the effectiveness and feasibility of the proposed methods. Findings – The results show that the proposed can solve the MAGDM problems within the context of 2-tuple linguistic information, in which the attributes are existing interaction phenomenon. Some 2-tuple aggregation operators based on MM have been developed. A case study of supplier selection is provided to illustrate the effectiveness and feasibility of the proposed methods. The results show that the proposed methods are useful to aggregate the linguistic decision information in which the attributes are not independent so as to select the most suitable supplier. Practical implications – The proposed methods can solve the 2-tuple linguistic MAGDM problem, in which the interactions exist among the attributes. Therefore, it can be used to supplier selection problems and other similar management decision problems. Originality/value – The paper develop some 2-tuple aggregation operators based on MM, and further present two methods based on the proposed operators for solving MAGDM problems. It is useful to deal with multiple attribute interaction decision-making problems and suitable to solve a variety of management decision-making applications.

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17

He, Wei, Lu, Wei, and Lin. "Pythagorean 2-Tuple Linguistic Taxonomy Method for Supplier Selection in Medical Instrument Industries." International Journal of Environmental Research and Public Health 16, no. 23 (December 3, 2019): 4875. http://dx.doi.org/10.3390/ijerph16234875.

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Supplier selection in medical instrument industries is a classical multiple attribute group decision making (MAGDM) problem. The Pythagorean 2-tuple linguistic sets (P2TLSs) can reflect uncertain or fuzzy information well and solve the supplier selection in medical instrument industries, and the original Taxonomy is very appropriate for comparing different alternatives with respect to their advantages from studied attributes. In this study, we present an algorithm that combines Pythagorean 2-tuple linguistic numbers (P2TLNs) with the Taxonomy method, where P2TLNs are applied to express the evaluation of decision makers on alternatives. Relying on the Pythagorean 2-tuple linguistic weighted average (P2TLWA) operator or Pythagorean 2-tuple linguistic weighted geometric (P2TLWG) operator to fuse P2TLNs, the new general framework is established for Pythagorean 2-tuple linguistic multiple attribute group decision making (MAGDM) under the classical Taxonomy method. Ultimately, an application case for supplier selection in medical instrument industries is designed to test the novel method’s applicability and practicality and a comparative analysis with three other methods is used to elaborate further.

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18

Wei, Guiwu, and Xiaofei Zhao. "METHODS FOR PROBABILISTIC DECISION MAKING WITH LINGUISTIC INFORMATION." Technological and Economic Development of Economy 20, no. 2 (June 28, 2014): 193–209. http://dx.doi.org/10.3846/20294913.2014.869515.

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Анотація:

With respect to decision making problems by using probabilities, immediate probabilities and information that can be represented with linguistic labels, some new decision analysis are proposed. Firstly, we shall develop three new aggregation operators: generalized probabilistic 2-tuple weighted average (GP-2TWA) operator, generalized probabilistic 2-tuple ordered weighted average (GP-2TOWA) operator and generalized immediate probabilistic 2-tuple ordered weighted average (GIP-2TOWA) operator. These operators use the weighted average (WA) operator, the ordered weighted average (OWA) operator, linguistic information, probabilistic information and immediate probabilistic information. They are quite useful because they can assess the uncertain information within the problem by using both linguistic labels and the probabilistic information that considers the attitudinal character of the decision maker. In these approaches, alternative appraisal values are calculated by the aggregation of 2-tuple linguistic information. Thus, the ranking of alternative or selection of the most desirable alternative(s) is obtained by the comparison of 2-tuple linguistic information. Finally, we give an illustrative example about selection of strategies to verify the developed approach and to demonstrate its feasibility and practicality.

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19

Ye, Ye, and Peide LIU. "SOME HERONIAN MEAN OPERATORS WITH 2-TUPLE LINGUISTIC INFORMATION AND THEIR APPLICATION TO MULTIPLE ATTRIBUTE GROUP DECISION MAKING." Technological and Economic Development of Economy 21, no. 5 (September 29, 2015): 797–814. http://dx.doi.org/10.3846/20294913.2015.1055614.

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Анотація:

With respect to multi-attribute group decision-making problems, in which attribute values take the form of 2-tuple linguistic information, a new decision making method that considers the interrelationships of attribute values is proposed. Firstly, some new aggregation operators of 2-tuple linguistic information based on Heronian mean are proposed, such as 2-tuple linguistic Heronian mean operator (2TLHM) and 2-tuple linguistic weighted Heronian mean operator (2TLWHB), and some desired properties of the proposed operators are studied. Then, a method based on the 2TLHM and 2TLWHB operators for multiple attribute group decision making is developed. In this approach, the interrelationships of attribute values are considered. Finally, an illustrative example is given to verify the developed approach and to demonstrate its practicality and effectiveness.

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20

Singh, Anjali, Anjana Gupta, and Aparna Mehra. "Matrix games with 2-tuple linguistic information." Annals of Operations Research 287, no. 2 (March 19, 2018): 895–910. http://dx.doi.org/10.1007/s10479-018-2810-6.

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21

Liu, Hu-Chen, Qing-Lian Lin, and Jing Wu. "Dependent Interval 2-Tuple Linguistic Aggregation Operators and Their Application to Multiple Attribute Group Decision Making." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 22, no. 05 (October 2014): 717–35. http://dx.doi.org/10.1142/s0218488514500366.

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Анотація:

Consider the various types of uncertain preference information provided by the decision makers and the importance of determining the associated weights for the aggregation operator, the multiple attribute group decision making (MAGDM) methods based on some dependent interval 2-tuple linguistic aggregation operators are proposed in this paper. Firstly some operational laws and possibility degree of interval 2-tuple linguistic variables are introduced. Then, we develop a dependent interval 2-tuple weighted averaging (DITWA) operator and a dependent interval 2-tuple weighted geometric (DITWG) operator, in which the associated weights only depend on the aggregated interval 2-tuple arguments and can relieve the influence of unfair arguments on the aggregated results by assigning low weights to them. Based on the DITWA and the DITWG operators, some approaches for multiple attribute group decision making with interval 2-tuple linguistic information are proposed. Finally, an illustrative example is given to demonstrate the practicality and effectiveness of the proposed approaches.

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22

Zhang, Ai Ping, and Tong Jun Zhan. "Modified Proportional 2-Tuple and its Application in Uncertainty Environment." Advanced Materials Research 981 (July 2014): 267–74. http://dx.doi.org/10.4028/www.scientific.net/amr.981.267.

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Анотація:

A modified proportional 2-tuple was proposed to apply to the term sets in that the distance of the adjacent tems is not equal,and the comparison methods as well as the aggregation operators were proposed too.And the modified proportional 2-tuple fuzzy linguistic representation model is extended to uncertainty modified proportional 2-tuple fuzzy linguistic representation model,and the new comparison rule and aggregation operators were provided.

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23

Feng, Min, and Yushui Geng. "Some Novel Picture 2-Tuple Linguistic Maclaurin Symmetric Mean Operators and Their Application to Multiple Attribute Decision Making." Symmetry 11, no. 7 (July 20, 2019): 943. http://dx.doi.org/10.3390/sym11070943.

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Анотація:

When solving multiple attribute decision making (MADM) problems, the 2-tuple linguistic variable is an effective tool that can not only express complex cognitive information but also prevent loss of information in calculation. The picture fuzzy set (PFS) has three degrees and has more freedom to express cognitive information. In addition, Archimedean t-conorm and t-norm (ATT) can generalize most existing t-conorms and t-norms and Maclaurin symmetric mean (MSM) operators can catch the relationships among the multi-input parameters. Therefore, we investigate several novel aggregation operators, such as the picture 2-tuple linguistic MSM (2TLMSM) operator based on the ATT (ATT-P2TLMSM) and the picture 2-tuple linguistic generalized MSM (2TLGMSM) operator based on ATT (ATT-P2TLGMSM). Considering that the input parameters have different importance, we proposed picture 2-tuple linguistic weighted MSM (2TLWMSM) operators based on ATT (ATT-P2TLWMSM) and picture 2-tuple linguistic weighted generalized MSM (2TLWGMSM) operators based on ATT (ATT-P2TLWGMSM). Finally, a MADM method is introduced, and an expositive example is presented to explain the availability and applicability of the developed operators and methods.

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24

Akram, Muhammad, Rabia Bibi, and Mohammed M. Ali Al-Shamiri. "A Decision-Making Framework Based on 2-Tuple Linguistic Fermatean Fuzzy Hamy Mean Operators." Mathematical Problems in Engineering 2022 (July 6, 2022): 1–29. http://dx.doi.org/10.1155/2022/1501880.

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Анотація:

Aggregation operators are useful tools for approaching situations in the realm of multiattribute decision-making (MADM). Among the most valuable aggregation strategies, the Hamy mean (HM) operator is designed to capture the correlations among integral parameters. In this article, a series of Hamy-inspired operators are used to combine 2-tuple linguistic Fermatean fuzzy (2TLFF) information. The new 2TLFF aggregation operators that are born from this adaptation include the 2-tuple linguistic Fermatean fuzzy Hamy mean (2TLFFHM) operator, 2-tuple linguistic Fermatean fuzzy weighted Hamy mean (2TFFWHM) operator, 2-tuple linguistic Fermatean fuzzy dual Hamy mean (2TLFFDHM) operator, and 2-tuple linguistic Fermatean fuzzy weighted Hamy mean (2TLFFWDHM) operator. Furthermore, various essential theorems are stated, and special cases of these operators are thoroughly examined. Then, a renewed multiattribute group decision-making (MAGDM) technique based on the suggested aggregation operators is provided. A practical example corroborates the usefulness and implementability of this technique. Finally, the merits of the proposed MAGDM method are demonstrated by comparing it with existing approaches, namely, it can deal with MAGDM problems by considering interactions among multiple attributes based on the 2TLFFWHM operator.

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Yuan, Fuchun. "Method for Pythagorean Interval 2-Tuple Linguistic Multiattribute Group Decision Making and Its Application to the Ship Navigation Environment Safety Assessment." Discrete Dynamics in Nature and Society 2022 (February 25, 2022): 1–11. http://dx.doi.org/10.1155/2022/6881900.

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In this paper, some fundamental theories of the Pythagorean interval 2-tuple linguistic numbers (PI2TLNs) combined with the EDAS (evaluation based on distance from average solution) method are proposed. Firstly, we introduced the original concepts of Pythagorean interval 2-tuple linguistic sets (PI2TLSs), and two aggregation operators of PI2TLN were also introduced. Then, the steps of the EDAS method were described briefly. Moreover, the PI2TLN-EDAS model was provided to address the multiattribute group decision-making (MAGDM) problem, and calculation steps were deduced in detail. The effectiveness of the method was illustrated by taking the ship navigation environment safety assessment as an example. Finally, we conducted comparative analysis between PI2TLN-EDAS method and Pythagorean interval 2-tuple linguistic weighted averaging (PI2TLWA) operator/Pythagorean interval 2-tuple linguistic weighted geometric (PI2TLWG) operator.

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Faizi, Shahzad, Tabasam Rashid, and Sohail Zafar. "A Multicriteria Decision-Making Approach Based on Fuzzy AHP with Intuitionistic 2-Tuple Linguistic Sets." Advances in Fuzzy Systems 2018 (August 1, 2018): 1–12. http://dx.doi.org/10.1155/2018/5789192.

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Анотація:

In the modern literature related to linguistic decision-making, the 2-tuple linguistic representation model and its useful applications in various fields have been extensively studied and used during the last decade. Recently, some useful multicriteria decision-making (MCDM) methods have been introduced based on fuzzy analytic hierarchy process (AHP) for 2-tuple linguistic representation model. By keeping in mind the importance of this linguistic model, in this paper, we introduce a fuzzy AHP methodology for intuitionistic 2-tuple linguistic sets (I2TLSs) which is a useful extension of the 2-tuple linguistic representation model. This study is comprised of four stages. In the first stage, we define some operational laws for I2TL elements (I2TLEs) and prove some related important properties. In the second stage, intuitionistic 2-tuple linguistic preference relation (I2TLPR) and multiplicative I2TLPR are defined using I2TLSs. In the 3rd stage, a transformation mechanism is introduced which can transform an I2TLPR to a corresponding intuitionistic preference relation (IPR) and vice versa. In the fourth stage, an approach is proposed for checking the consistency of an I2TLPR and presented a method to repair the inconsistent one by using the proposed transformation mechanism. Finally, a numerical example is given and comparative analysis is carried out with the TOPSIS method to verify the validity of the proposed method.

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Khan, Arshad Ahmad, Muhammad Qiyas, Saleem Abdullah, Jianchao Luo, and Mahwish Bano. "Analysis of Robot Selection Based on 2-Tuple Picture Fuzzy Linguistic Aggregation Operators." Mathematics 7, no. 10 (October 21, 2019): 1000. http://dx.doi.org/10.3390/math7101000.

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Анотація:

The aim of this article is to propose the 2-tuple picture fuzzy linguistic aggregation operators and a decision-making model to deal with uncertainties in the form of 2-tuple picture fuzzy linguistic sets; 2-tuple picture fuzzy linguistic operators have more flexibility than general fuzzy set. We proposed a number of aggregation operators, namely, 2-TPFLWA, 2-TPFLOWA, 2-TPFLHA, 2-TPFLWG, 2-TPFLOWG, and 2-TPFLHG operators. The distinguished feature of the developed operators are studied. At that point, we used these operators to design a model to deal with multiple attribute decision-making issues under the 2-tuple picture fuzzy linguistic information. Then, a practical application of robot selection by manufacturing unit is given to prove the introduced technique and to show its practicability and effectiveness. Besides this, a systematic comparison analysis with other existent approaches is conducted to reveal the advantage of our developed method. Results indicate that the proposed method is suitable and effective for decision-making problems.

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YANG, WEI. "INDUCED CHOQUET INTEGRALS OF 2-TUPLE LINGUISTIC INFORMATION." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 21, no. 02 (April 2013): 175–200. http://dx.doi.org/10.1142/s0218488513500104.

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Анотація:

The group decision making problem with inter-dependent or interactive attributes is studied. By using the Choquet integral and the inducing variables, we develop the induced 2-tuple correlated averaging (ITCA) operator, the generalized induced 2-tuple correlated averaging (GITCA) operator and the quasi-arithmetic induced 2-tuple correlated averaging (QITCA) operator. The characteristics of the proposed operators are that the evaluation values of decision makers are in linguistic arguments, the correlations among the elements can be reflected and the ordering of the arguments is based on other associated variables instead of their own values. The properties of these operators are studied and new multiple attribute decision making method based on the new operators is proposed. Finally, architecture material supplier selection problem is provided to illustrate the feasibility and efficiency of the proposed method.

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Tang, Shujue. "A TODIM Method Based on 2- Tuple Linguistic Neutrosophic Numbers and Its Application." Journal of Innovation and Development 2, no. 3 (April 12, 2023): 78–83. http://dx.doi.org/10.54097/jid.v2i3.7280.

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Анотація:

This paper proposes a TODIM method based on 2-Tuple Linguistic Neutrosophic Numbers for the decision-making problem of bounded rational online shopping consumers. Firstly, the definition of 2- Tuple Linguistic Neutrosophic sets, normalized Hamming distance and the operation method of traditional TODIM method are introduced. Then the paper puts forward the operation steps of TODIM method based on 2-Tuple Linguistic Neutrosophic Numbers. Finally, an actual example analysis application is carried out to illustrate the operability and rationality of the method. Suggestions on recommendation function of shopping website and online business operators are put forward.

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Wang, Huijuan, Xin Wang, and Lidong Wang. "Multicriteria Decision Making Based on Archimedean Bonferroni Mean Operators of Hesitant Fermatean 2-Tuple Linguistic Terms." Complexity 2019 (December 20, 2019): 1–19. http://dx.doi.org/10.1155/2019/5705907.

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Анотація:

The study is concerned with the representation and aggregation of complex uncertainty information. First, the concept of hesitant Fermatean 2-tuple linguistic sets (HF2TLSs) is introduced for characterizing an individual’s imprecision preferences and assessing information by combining 2-tuple linguistic terms and Fermatean fuzzy sets. The advantage of hesitant Fermatean 2-tuple linguistic information is that it can handle higher levels of uncertainty and express the decision-makers’ hesitancy. Second, we extend Bonferroni mean (BM) operators under the background of HF2TLSs for the sake of their application in information fusion and decision making. The Archimedean t-norm and s-norm- (ATS-) based hesitant Fermatean 2-tuple linguistic weighted Bonferroni mean (A-HF2TLWBM) operator and the ATS-based hesitant Fermatean 2-tuple linguistic weighted geometric Bonferroni mean (A-HF2TLWGBM) operator are developed by considering the interrelationship between any two variables. The main benefit of the proposed operators is that these operators deliver more complete and flexible results compared to existing methods. Moreover, some fundamental properties and special cases are examined by adjusting parameter values. Finally, an approach is designed as a support for handling decision making problems, and an example regarding investment selection is provided to demonstrate the practicality of the designed method with a detailed discussion of parameter influence and comparisons with the existing methods.

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Fan, Jianping, Feng Yan, and Meiqin Wu. "GLDS method for multiple attribute group decision making under 2-Tuple linguistic neutrosophic environment." Journal of Intelligent & Fuzzy Systems 40, no. 6 (June 21, 2021): 11523–38. http://dx.doi.org/10.3233/jifs-202748.

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Анотація:

In this article, the gained and lost dominance score (GLDS) method is extended into the 2-tuple linguistic neutrosophic environment, which also combined the power aggregation operator with the evaluation information to deal with the multi-attribute group decision-making problem. Since the power aggregation operator can eliminate the effects of extreme evaluating data from some experts with prejudice, this paper further proposes the 2-tuple linguistic neutrosophic numbers power-weighted average operator and 2-tuple linguistic neutrosophic numbers power-weighted geometric operator to aggregate the decision makers’ evaluation. Moreover, a model based on the score function and distance measure of 2-tuple linguistic neutrosophic numbers (2TLNNs) is developed to get the criteria weights. Combing the GLDS method with 2-tuple linguistic neutrosophic numbers and developing a 2TLNN-GLDS method for multiple attribute group decision making, it can express complex fuzzy information more conveniently in a qualitative environment and also consider the dominance relations between alternatives which can get more effective results in real decision-making problems. Finally, an applicable example of selecting the optimal low-carbon logistics park site is given. The comparing results show that the proposed method outperforms the other existing methods, as it can get more reasonable results than others and it is more convenient and effective to express uncertain information in solving realistic decision-making problems.

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Feng, Min, Peide Liu, and Yushui Geng. "A Method of Multiple Attribute Group Decision Making Based on 2-Tuple Linguistic Dependent Maclaurin Symmetric Mean Operators." Symmetry 11, no. 1 (January 1, 2019): 31. http://dx.doi.org/10.3390/sym11010031.

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Анотація:

Aiming at multiple attribute group decision making (MAGDM) problems, especially the attribute values of 2-tuple linguistic numbers and the interrelationships between each attribute needing to be considered, this paper proposes a new method of analysis. Firstly, we developed a few new aggregation operators, like the 2-tuple linguistic dependent weighted Maclaurin symmetric mean (2TLDWMSM) operator, the 2-tuple linguistic dependent weighted generalized Maclaurin symmetric mean (2TLDWGMSM) operator, and the 2-tuple linguistic dependent weighted geometric Maclaurin symmetric mean (2TLDWGeoMSM) operator. In the above operators, Maclaurin symmetric mean (MSM) operators can take the relationships between each attribute into account and dependent operators can mitigate the unfair parameters’ impact on the overall outcome, in which those ‘‘incorrect’’ and ‘‘prejudiced’’ parameters are distributed with low weights. Next, a method used by the 2TLDWMSM, 2TLDWGMSM, and 2TLDWGeoMSM operators for MAGDM is introduced. Finally, there is an explanative example to confirm the proposed approach and explain its availability and usefulness.

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Singh, Anjali, and Anjana Gupta. "Matrix Games with Interval-Valued 2-Tuple Linguistic Information." Games 9, no. 3 (September 2, 2018): 62. http://dx.doi.org/10.3390/g9030062.

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Анотація:

In this paper, a two-player constant-sum interval-valued 2-tuple linguistic matrix game is construed. The value of a linguistic matrix game is proven as a non-decreasing function of the linguistic values in the payoffs, and, hence, a pair of auxiliary linguistic linear programming (LLP) problems is formulated to obtain the linguistic lower bound and the linguistic upper bound of the interval-valued linguistic value of such class of games. The duality theorem of LLP is also adopted to establish the equality of values of the interval linguistic matrix game for players I and II. A flowchart to summarize the proposed algorithm is also given. The methodology is then illustrated via a hypothetical example to demonstrate the applicability of the proposed theory in the real world. The designed algorithm demonstrates acceptable results in the two-player constant-sum game problems with interval-valued 2-tuple linguistic payoffs.

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Zhang, Huarong, and Xiangqian Feng. "A Fuzzy Evaluation Approach for Scientific Research Projects with 2-Tuple Linguistic Preference Relations." Frontiers in Business, Economics and Management 2, no. 3 (December 7, 2021): 43–45. http://dx.doi.org/10.54097/fbem.v2i3.188.

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Science and technology project evaluation is an important means of science and technology management. Whether the evaluation of science and technology projects is fair or not directly affects the development of national economy and the allocation of science and technology resources. Due to the complexity of the project and the fuzziness of human thinking, the expert information is often difficult to quantify in the process of project evaluation. Generally, the better choice is to express it in qualitative language. In this paper, the 2-tuple linguistic preference relation is proposed to evaluate scientific research projects. The reasonableness of the concept of complete consistency for the 2-tuple linguistic preference relation is discussed. Priority of 2-tuple linguistic preference relation is set up based on the 2-tuple weighted geometric averaging operator. Finally, combined with Science and technology project evaluation problem, the effectiveness and feasibility of the method are verified.

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35

Qiyas, Muhammad, Muhammad Naeem, Lazim Abdullah, Muhammad Riaz, and Neelam Khan. "Decision Support System Based on Complex Fractional Orthotriple Fuzzy 2-Tuple Linguistic Aggregation Operator." Symmetry 15, no. 1 (January 16, 2023): 251. http://dx.doi.org/10.3390/sym15010251.

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Анотація:

In this research, we provide tools to overcome the information loss limitation resulting from the requirement to estimate the results in the discrete initial expression domain. Through the use of 2-tuples, which are made up of a linguistic term and a numerical value calculated between [0.5,0.5), the linguistic information will be expressed. This model supports continuous representation of the linguistic data within its scope, permitting it to express any information counting received through an aggregation procedure. This study provides a novel approach to develop a linguistic multi-attribute group decision-making (MAGDM) approach with complex fractional orthotriple fuzzy 2-tuple linguistic (CFOF2TL) assessment details. Initially, the concept of a complex fractional orthotriple fuzzy 2-tuple linguistic set (CFO2TLS) is proposed to convey uncertain and fuzzy information. In the meantime, simple aggregation operators, such as CFOF2TL weighted average and geometric operators, are defined. In addition, the CFOF2TL Maclaurin’s symmetric mean (CFOF2TLMSM) operators and their weighted shapes are presented, and their attractive characteristics are also discussed. A new MAGDM approach is built using the developed aggregation operators to address managing economic crises under COVID-19 with the CFOF2TL information. As a result, the effectiveness and robustness of the developed method are accompanied by an empirical example, and a comparative study is carried out by contrasting it with previous approaches.

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36

Wang, Yan-Mei. "Approaches to Multiple Attribute Group Decision Making Based on the DTOWHA Operator with 2-Tuple Linguistic Information." Journal of Computational and Theoretical Nanoscience 13, no. 10 (October 1, 2016): 7314–18. http://dx.doi.org/10.1166/jctn.2016.5716.

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Анотація:

We investigate the multiple attribute group decision making (MAGDM) problems in which the attribute values take the form of 2-tuple linguistic information. In this paper, we develop the dependent 2-tuple ordered weighted harmonic averaging (DTOWHA) operator, and then apply the DTOWHA operator to develop some approaches for multiple attribute group decision making with 2-tuple linguistic information. Finally, an illustrative example for service quality assessment in special higher education is given to verify the developed approach and to demonstrate its practicality and effectiveness.

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37

Dong, Yucheng, Wei-Chiang Hong, and Yinfeng Xu. "Measuring consistency of linguistic preference relations: a 2-tuple linguistic approach." Soft Computing 17, no. 11 (March 28, 2013): 2117–30. http://dx.doi.org/10.1007/s00500-013-1031-9.

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38

Romo-Lozano, José L., Rosa M. Rodríguez, Roberto Rendón-Medel, and Álvaro Labella. "Application of a multigranular approach based on the 2-tuple fuzzy linguistic model for the evaluation of forestry policy indicators." Revista Chapingo Serie Ciencias Forestales y del Ambiente 27, no. 2 (2020): 257–75. http://dx.doi.org/10.5154/r.rchscfa.2020.06.043.

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Introduction: The need for quality indicators is well recognized by users and proponents of public policy evaluation. Indicators recurrently include qualitative attributes for which there are few studies assessing the level of compliance. Objective: To apply a multigranular approach, based on the 2-tuple fuzzy linguistic model, to evaluate 13 indicators of the National Forestry Program, established in the system of social policy indicators derived from the National Development Plan 2012-2018 of Mexico. Materials and methods: The method uses the 2-tuple fuzzy linguistic representation model and an extension called extended linguistic hierarchies, designed to solve problems with multigranular linguistic information. The indicators’ level of compliance was evaluated based on four criteria: clarity, relevance, monitoring, and adequacy. Results and discussion: The structure defined in evaluating social policy indicators corresponds appropriately to that used with the 2-tuple fuzzy linguistic model. The evaluation resulted in a sorted list in which the indicator “Rate of change of timber forest production” had the best rating with a “very high” level of compliance; 10 other indicators had the “high” level of compliance, and the remaining two indicators were rated with “moderate” compliance. Conclusions: The 2-tuple fuzzy linguistic model allowed the appropriate evaluation of the level of compliance with the desirable attributes of indicators

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Akram, Muhammad, Sumera Naz, Feng Feng, Ghada Ali, and Aqsa Shafiq. "Extended MABAC method based on 2-tuple linguistic $ T $-spherical fuzzy sets and Heronian mean operators: An application to alternative fuel selection." AIMS Mathematics 8, no. 5 (2023): 10619–53. http://dx.doi.org/10.3934/math.2023539.

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<abstract>In recent years, fossil fuel resources have become increasingly rare and caused a variety of problems, with a global impact on economy, society and environment. To tackle this challenge, we must promote the development and diffusion of alternative fuel technologies. The use of cleaner fuels can reduce not only economic cost but also the emission of gaseous pollutants that deplete the ozone layer and accelerate global warming. To select an optimal alternative fuel, different fuzzy decision analysis methodologies can be utilized. In comparison to other extensions of fuzzy sets, the $ T $-spherical fuzzy set is an emerging tool to cope with uncertainty by quantifying acceptance, abstention and rejection jointly. It provides a general framework to unify various fuzzy models including fuzzy sets, picture fuzzy sets, spherical fuzzy sets, intuitionistic fuzzy sets, Pythagorean fuzzy sets and generalized orthopair fuzzy sets. Meanwhile, decision makers prefer to employ linguistic terms when expressing qualitative evaluation in real-life applications. In view of these facts, we develop an extended multi-attributive border approximation area comparison (MABAC) method for solving multiple attribute group decision-making problems in this study. Firstly, the combination of $ T $-spherical fuzzy sets with 2-tuple linguistic representation is presented, which provides a general framework for expressing and computing qualitative evaluation. Secondly, we put forward four kinds of 2-tuple linguistic $ T $-spherical fuzzy aggregation operators by considering the Heronian mean operator. We investigate some fundamental properties of the proposed 2-tuple linguistic $ T $-spherical fuzzy aggregation operators. Lastly, an extended MABAC method based on the 2-tuple linguistic $ T $-spherical fuzzy generalized weighted Heronian mean and the 2-tuple linguistic $ T $-spherical fuzzy weighted geometric Heronian mean operators is developed. For illustration, a case study on fuel technology selection with 2-tuple linguistic $ T $-spherical fuzzy information is also conducted. Moreover, we show the validity and feasibility of our approach by comparing it with several existing approaches.</abstract>

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Akram, Muhammad, Naila Ramzan, Anam Luqman, and Gustavo Santos-García. "An integrated MULTIMOORA method with 2-tuple linguistic Fermatean fuzzy sets: Urban quality of life selection application." AIMS Mathematics 8, no. 2 (2022): 2798–828. http://dx.doi.org/10.3934/math.2023147.

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Анотація:

<abstract>This article elaborates the enormous theory of MULTIMOORA (multi-objective optimization ratio analysis plus full multiplicative form) method to build up a new outranking approach for the innovative extension of fuzzy set theory, namely, 2-tuple linguistic Fermatean fuzzy sets (2TLFFSs). The main objective of the proposed work is to expand and present the components of MULTIMOORA method in 2-tuple linguistic Fermatean fuzzy framework. The resulted technique is named as 2-tuple linguistic Fermatean fuzzy MULTIMOORA method. This technique is designed to tackle the unclear information using 2-tuple linguistic Fermatean fuzzy numbers (2TLFFNs). The proposed model is intrinsically superior to deal with one-dimensional linguistic data. The 2TLFF-MULTIMOORA method takes into account standard relative correlations. Also, it handles the rank inversion problem when changing the rank of alternatives by adding one or more alternatives. The algorithm designed for the proposed methodology is elaborated with a numerical example (to opt for the most favorable city for the selection of quality of life). The accuracy and precision of the proposed strategy is determined by narrating a comparative study. Finally, the advantages of the developed technique over existing methods are discussed briefly.</abstract>

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Zhang, Siqi, Hui Gao, Guiwu Wei, Yu Wei, and Cun Wei. "Evaluation Based on Distance from Average Solution Method for Multiple Criteria Group Decision Making under Picture 2-Tuple Linguistic Environment." Mathematics 7, no. 3 (March 8, 2019): 243. http://dx.doi.org/10.3390/math7030243.

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Анотація:

In this paper, we design the EDAS (evaluation based on distance from average solution) model with picture 2-tuple linguistic numbers (P2TLNs). First, we briefly reviewed the definition of P2TLSs and introduced the score function, accuracy function, and operational laws of P2TLNs. Then, we combined the traditional EDAS model for multiple criteria group decision making (MCGDM) with P2TLNs. Our presented model was more accurate and effective for considering the conflicting attributes. Finally, a numerical case for green supplier selection was given to illustrate this new model, and some comparisons were also conducted between the picture 2-tuple linguistic weighted averaging (P2TLWA), picture 2-tuple linguistic weighted geometric (P2TLWG) aggregation operators and EDAS model with P2TLNs, to further illustrate the advantages of the new method.

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42

Liu, Yi, Jun Liu, Ya Qin, and Yang Xu. "A Novel Method Based on Extended Uncertain 2-tuple Linguistic Muirhead Mean Operators to MAGDM under Uncertain 2-Tuple Linguistic Environment." International Journal of Computational Intelligence Systems 12, no. 2 (2019): 498. http://dx.doi.org/10.2991/ijcis.d.190315.001.

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43

Xie, Yi, and Rong Ran. "A Study on Enterprise Technological Innovation Capability Evaluation with 2-Tuple Linguistic Information." Journal of Computational and Theoretical Nanoscience 13, no. 10 (October 1, 2016): 7347–50. http://dx.doi.org/10.1166/jctn.2016.5724.

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Анотація:

Today rapid and drastic changes are taking place in technology. Technological innovation capability of a nation to knowledge becomes the crucial factor which raises national industry competition ability. Only in this way can an enterprise scientifically realize its technological innovation ability in its competition with its counterpart, employ appropriate innovation strategy, make full use of its advantages and achieve the best economic and social benefits. The aim of this paper is to study the evaluation problems for evaluating the enterprise technological innovation capability with 2-tuple linguistic information. The induced 2-tuple linguistic choquet ordered harmonic average (I-2TCOHA) operator is used to aggregate the 2-tuple linguistic information corresponding to each alternative and rank the alternatives and select the most desirable one(s). Finally an illustrative example for evaluating the enterprise technological innovation capability has been given to show the developed approach.

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Zhou, Sheng Han, Wen Bing Chang, and Ze Jian Xiong. "Risk Assessment Model with 2-Tuple Temporal Linguistic Variable." Applied Mechanics and Materials 58-60 (June 2011): 2540–45. http://dx.doi.org/10.4028/www.scientific.net/amm.58-60.2540.

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Анотація:

The paper aims to develop a risk assessment model with the fuzzy temporal information. The traditional model assess risk with the risk matrix method. And the method rank the risks without regard to the with the temporal information to assess the risk. The model integrates the method of 2-tuple linguistic and temporal linguistic variable. The improved concept defines the transition symbols operator as the projection of temporal term on the fuzzy linguistic variable. The new model may deal with the temporal information in the fuzzy linguistic judgements. The emprical research give a example by applying the new method. The result of example show that the new model can provide the worthwhile temporal information in the assessment result. temporal element temporal element temporal element temporal element

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45

He, Tingting, Siqi Zhang, Guiwu Wei, Rui Wang, Jiang Wu, and Cun Wei. "CODAS METHOD FOR 2-TUPLE LINGUISTIC PYTHAGOREAN FUZZY MULTIPLE ATTRIBUTE GROUP DECISION MAKING AND ITS APPLICATION TO FINANCIAL MANAGEMENT PERFORMANCE ASSESSMENT." Technological and Economic Development of Economy 26, no. 4 (June 22, 2020): 920–32. http://dx.doi.org/10.3846/tede.2020.11970.

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Анотація:

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.

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Mi, Chuanmin, Xiaofei Shan, Yuan Qiang, Yosa Stephanie, and Ye Chen. "A new method for evaluating tour online review based on grey 2-tuple linguistic." Kybernetes 43, no. 3/4 (April 1, 2014): 601–13. http://dx.doi.org/10.1108/k-06-2013-0123.

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Анотація:

Purpose – Tour social network data that are heterogeneous contain not only the quantitative structured evaluation data, but also the qualitative non-structured data. This is a big data scenario. How to evaluate tour online review and then recommend to potential tourists quickly and accurately are important parts of social responsibility of tour companies. The purpose of this paper is to propose a new method for evaluating tour online review based on grey 2-tuple linguistic. Design/methodology/approach – The phenomenon of “poor information” exists in some big data scenario. According to social responsibility, grey 2-tuple linguistic evaluation model for tour online review is proposed. Findings – Tour social networks contain data that are valuable to each individual on tourism industry's value chain. Grey 2-tuple linguistic evaluation model can be used for evaluating tour online reviews. This is a systems thinking method that takes social responsibility into account. Research limitations/implications – Due to the complex links among reviewers in social network, network mining approaches and models are expected to be added to this research in the near future. Practical implications – Grey 2-tuple linguistic evaluation method can contribute to the future research on evaluating a variety of tour social network comment data in the real world. Originality/value – A new evaluation method for making evaluation and recommendations based on tour social network comment information is proposed.

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Zhang, Huaige, Xianpei Hong, Qing Li, Yeming Gong, and Shan Liu. "Exploring the Intellectual Structure and International Cooperation in Information Management." Journal of Global Information Management 29, no. 6 (November 2021): 1–20. http://dx.doi.org/10.4018/jgim.294577.

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Анотація:

To make a comprehensive literature review and identify the development trends, this study maps the intellectual structure of the research information management based on co-keyword analysis, the 2-tuple linguistic technique, and social network analysis. This study reveals the intellectual structure by analyzing the topological structure, conceptual structure, and strategic diagram. From the perspective of topological structure, the research of the information management field can be divided into three layers including the nucleus layer, middle layer, and marginal layer. In terms of the conceptual structure, the research of information management can be divided into four sub-fields including health information management, information systems, information technology, and information management application. The four subfields can be repartitioned into seven clusters by using a 2-tuple linguistic model, which means that the 2-tuple linguistic model can improve co-keyword analysis.

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Liu, Xiao-Feng. "Assessment of Residential Building Energy-Saving with 2-Tuple Linguistic Information." Journal of Computational and Theoretical Nanoscience 13, no. 10 (October 1, 2016): 7390–93. http://dx.doi.org/10.1166/jctn.2016.5731.

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Анотація:

With the acceleration of the process of our country’s urbanization, the investment of urban infrastructure construction continues to increase and the construction industry has become a pillar industry of the national economy. However, the proportion of building energy consumption in the total energy is increasing at the same time. In order to achieve the sustainable development of the society, the energy-saving target is proposed in the 12th Five-Year Plan of China, which sets for the requirements for building energy-saving in Shaanxi Province. Evaluation of building energy-saving is an effective method to promote the healthy development of the work of building energy efficiency, but there is not a complete, reasonable and practicable the evaluation system. In this paper, we investigate the multiple attribute group decision making (MAGDM) problems for evaluating the residential building energy-saving with 2-tuple linguistic information. Then, a model based on the 2-tuple weighted geometric (TWG) operator to evaluate the residential building energy-saving is presented. In this model, alternative appraisal values are calculated by the aggregation of 2-tuple linguistic information. Thus, the ranking of alternative or selection of the most desirable trip(s) is obtained by the comparison of 2-tuple linguistic information. Finally, an illustrative example for evaluating the residential building energy-saving is given to verify the developed approach and to demonstrate its practicality and effectiveness.

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Xiuhong Wang. "Model for Tourism Management with 2-tuple Linguistic Information." INTERNATIONAL JOURNAL ON Advances in Information Sciences and Service Sciences 3, no. 4 (May 31, 2011): 34–39. http://dx.doi.org/10.4156/aiss.vol3.issue4.5.

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Zhang, Zhihui, Fajie Wei, and Shenghan Zhou. "Approaches to comprehensive evaluation with 2-tuple linguistic information." Journal of Intelligent & Fuzzy Systems 28, no. 1 (2015): 469–75. http://dx.doi.org/10.3233/ifs-141323.

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