2-tuple Linguistic Information Research Articles

On Novel Operational Laws and Aggregation Operators of Picture 2-Tuple Linguistic Information for MCDM Problems

This paper primarily focuses on multi-criteria decision-making (MCDM) based on picture 2-tuple linguistic information. Since the picture 2-tuple linguistic set is structured by a linguistic 2-tuple and a picture fuzzy set, we first point out the inappropriateness of existing operations relating to picture fuzzy numbers and picture 2-tuple linguistic numbers. For the purpose of improving these misleading computations, we further propose novel operational laws for picture 2-tuple linguistic numbers from a correct version. Counterexamples, which are in one-to-one correspondence with the listed counterintuitive cases, are furnished to illustrate the limitations of existing operations and prove the feasibility of our newly presented operations. Moreover, by applying the novel operations, we put forward some modified aggregation operators which are further employed to a handling method for the MCDM problem with a picture 2-tuple linguistic matrix. Finally, two comparative and illustrative examples are furnished to verify the applicability and advantages of the proposed method.

Multiattribute group decision making based on intuitionistic 2-tuple linguistic information

In this paper, we propose a new method for multiattribute group decision making (MAGDM) with the intuitionistic 2-tuple linguistic (I2L) information based on the proposed I2L generalized aggregation (I2LGA) operator. Firstly, we extend the Archimedean T-norm (TN) and T-conorm (TC) from the range [0, 1] to [0, t] (t > 0), and propose the extended TN and TC. Then, we develop general operational laws for the I2L information (I2LI) and propose the I2L generalized aggregation (I2LGA) operator for the I2LI based on extended TN and TC, and give some special cases and some of their properties with respect to some types of the extended TN and TC. Then, we propose a new MAGDM method with the I2LI based on the proposed I2LGA operator. Finally, we use an application example to verify the validity of the proposed MAGDM method and to show its advantages compared to existing MAGDM methods.

Model for evaluating the visual design quality with 2-tuple linguistic information

Model for evaluating the visual design quality with 2-tuple linguistic information

Interval-valued intuitionistic linguistic multi-criteria group decision-making method based on the interval 2-tuple linguistic information

Interval-valued intuitionistic linguistic multi-criteria group decision-making method based on the interval 2-tuple linguistic information

A Method for Multi-Criteria Group Decision Making with 2-Tuple Linguistic Information Based on Cloud Model

This paper presents a new approach to solve the multi-criteria group decision making (MCGDM) problem where criteria values take the form of 2-tuple linguistic information. Firstly, a 2-tuple hybrid ordered weighted geometric (THOWG) operator is proposed, which synthetically considers the importance of both individual and the ordered position so as to overcome the defects of existing operators. Secondly, combining the advantages of the cloud model and 2-tuple linguistic variable, a new generating cloud method is proposed to transform 2-tuple linguistic variables into clouds. Thirdly, we further define some new cloud algorithms, such as cloud possibility degree and cloud support degree which can be respectively used to compare clouds and determine the criteria weights. Furthermore, a new approach for 2-tuple linguistic group decision making is presented on the basis of the THOWG operator, the improved generating cloud method as well as the new cloud algorithms. Finally, an example of assessing the social effects of biomass power plants (BPPS) is illustrated to verify the application and feasible of the developed approach, and a comparative analysis is also conducted to validate the effectiveness of the proposed method.

Model for evaluating the green supply chain performance under low-carbon agricultural economy environment with 2-tuple linguistic information

Model for evaluating the green supply chain performance under low-carbon agricultural economy environment with 2-tuple linguistic information

Method of Multiple Attribute Group Decision Making Based on 2-Dimension Interval Type-2 Fuzzy Aggregation Operators with Multi-granularity Linguistic Information

This paper proposes an approach to linguistic multiple attribute group decision-making (MAGDM) problems with 2-dimension multi-granularity linguistic information by adding a subjective imprecise estimation of reliability of the linguistic assessment information for expressing fuzzy information appropriately. To avoid the drawback of traditional transformation functions of multi-granularity linguistic information (MGLI) defined in the basic linguistic term set or 2-tuple linguistic information, in this paper, decision information is fully expressed by using 2-dimension interval type-2 trapezoidal fuzzy number (2DIT2TFN) representation model under multi-granular linguistic contexts. Firstly, the definition, operational laws, and ranking method of 2DIT2TFNs are proposed. Then 2-dimension interval type-2 trapezoidal fuzzy ordered weighted average (2DIT2TFOWA) operator and quasi-2-dimension interval type-2 trapezoidal fuzzy ordered weighted average (quasi-2DIT2TFOWA) operator are put forward. Moreover, we apply new operators to developing approach to MAGDM problem with linguistic term set of different odd cardinalities. Finally, a numerical example related to health management is provided to illustrate the utility and effectiveness of the developed method. We also make comparisons between the methods proposed in this paper and some existing ones to confirm its feasibility and rationality. The main contribution of this paper possesses three points: (1) proposing the 2DIT2TFNs, which can reflect the evaluation on objects more reasonably; (2) developing some new aggregation operators under 2-dimension interval type-2 trapezoidal fuzzy environment; and (3) applying new operators to developing approach to MAGDM problem with MGLI.

Comprehensive Evaluation on Employee Satisfaction of Mine Occupational Health and Safety Management System Based on Improved AHP and 2-Tuple Linguistic Information

In order to comprehensively evaluate the employee satisfaction of mine occupational health and safety management system, an analytic method based on fuzzy analytic hierarchy process and 2-tuple linguistic model was established. Based on the establishment of 5 first-grade indicators and 20 second-grade ones, method of improved AHP and the time-ordered Weighted Averaging Operator (T-OWA) model is constructed. The results demonstrate that the employee satisfaction of the mine occupational health and safety management system is of the ‘general’ rank. The method including the evaluation of employee satisfaction and the quantitative analysis of language evaluation information ensures the authenticity of the language evaluation information.

Comprehensive evaluation of regional economy development level in Jiangsu Province with 2-tuple linguistic information

Comprehensive evaluation of regional economy development level in Jiangsu Province with 2-tuple linguistic information

Research on the performance evaluation of experiment platforms with 2-tuple linguistic information

Research on the performance evaluation of experiment platforms with 2-tuple linguistic information

Human-machine function allocation method for aircraft cockpit based on interval 2-tuple linguistic information

Human-machine function allocation method for aircraft cockpit based on interval 2-tuple linguistic information

Picture 2-Tuple Linguistic Bonferroni Mean Operators and Their Application to Multiple Attribute Decision Making

In this paper, we investigate the multiple attribute decision-making problems with picture 2-tuple linguistic information. Then, we utilize Bonferroni mean and geometric Bonferroni mean operations to develop some picture 2-tuple linguistic aggregation operators: picture 2-tuple linguistic Bonferroni mean operator and picture 2-tuple linguistic geometric Bonferroni mean operator. Some desired properties and special cases of the developed operators are discussed in detail. Furthermore, considering the importance of the input arguments, we propose the picture 2-tuple linguistic weighted Bonferroni mean operator and picture 2-tuple linguistic weighted geometric Bonferroni mean operator. Finally, a practical example for selecting the service outsourcing provider of communications industry is given to verify the developed approach and to demonstrate its practicality and effectiveness.

Picture 2-tuple linguistic aggregation operators in multiple attribute decision making

In this paper, we investigate the multiple attribute decision-making problems with picture 2-tuple linguistic information. Then, we utilize arithmetic and geometric operations to develop several picture 2-tuple linguistic aggregation operators. The prominent characteristic of these proposed operators is studied. Then, we have utilized these operators to develop some approaches to solving 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.

Assessment of Residential Building Energy-Saving with 2-Tuple Linguistic Information

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.

Approaches to Multiple Attribute Group Decision Making Based on the DTOWHA Operator with 2-Tuple Linguistic Information

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.

A Study on Enterprise Technological Innovation Capability Evaluation with 2-Tuple Linguistic Information

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.

A MAGDM Method Based on 2-Tuple Linguistic Heronian Mean and New Operational Laws

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.

A novel model for enterprise technological innovation capability evaluation with 2-tuple linguistic information

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.

Energy planning problems with interval-valued 2-tuple linguistic information

In this paper, we address to the concern as to which alternative is most suitable for energy production in a new power plant set up in India. We model this problem as a multi-criteria group decision making problem where the criteria values are described in terms of interval-valued 2-tuple linguistic variables. We propose to solve this model by extending the PROMETHEE II method to interval-valued 2-tuple linguistic variables where the criteria weights in the PROMETHEE II method are supplied using the entropy measure. A small example is presented to illustrate the practicality and usefulness of the proposed method.

Development of some linguistic aggregation operators with conservation of interaction between criteria and their application in multiple attribute group decision problems

Decision making problems with fuzzy linguistic information and Choquet integral is investigated in this paper, to introduce three new aggregation operators: 2-tuple choquet integral averaging operator (TCIA), 2-tuple ordered choquet integral averaging operator (TOCIA) and combined 2-tuple choquet integral averaging operator which can be used to aggregate preference information that takes not only the form of linguistic variables but also study some of its desirable properties. Also, we developed a practical method based on TCIA as well as TOCIA operators for multiple attribute group decision making. Furthermore, in this approach alternative assessments are computed by the aggregation of 2-tuple linguistic information. Therefore, ranking alternatives or selecting the most desirable ones will be the outcome of the comparison between the 2-tuple linguistic information. Ultimately, the demonstration of the developed approaches, its practicality and its effectiveness is proved by a numerical example and a comparison with results issued from Wan method (Knowl-Based Syst 45:31–40, 2013).