2-tuple Linguistic Information Research Articles

TODIM method for multiple attribute decision making with 2-tuple linguistic pythagorean fuzzy information

TODIM method for multiple attribute decision making with 2-tuple linguistic pythagorean fuzzy information

EDAS method for multiple criteria group decision making under 2-tuple linguistic neutrosophic environment

In this paper, we present 2-tuple linguistic neutrosophic EDAS model based on traditional EDAS (Evaluation based on Distance from Average Solution) model and some fundamental theories of 2-tuple linguistic neutrosophic information. Firstly, we brief

A 2-tuple integrated DEA-based approach for neuromarketing technology evaluation

Purpose Neuromarketing, which is an interdisciplinary area, concentrates on evaluating consumers’ cognitive and emotional reactions to different marketing stimuli. In spite of advantages, neuromarketing still requires development and lacks a strong theoretical framework. Techniques that are used in neuromarketing studies have different superiorities and limitations, and thus, there is a need for the evaluation of the relevance of these techniques. The purpose of this study is to introduce a novel integrated approach for the neuromarketing research area. Design/methodology/approach The proposed approach combines 2-tuple linguistic representation model and data envelopment analysis to obtain the most efficient neuromarketing technique. It is apt to handle information provided by using both linguistic and numerical scales with multiple information sources. Furthermore, it allows managers to deal with heterogeneous information, without loss of information. Findings The proposed approach indicates that functional magnetic resonance imaging (fMRI) is the best performing neuromarketing technology. Recently, fMRI has been widely used in neuromarketing research. In spite of its high cost, its main superiorities are improved spatial and temporal resolutions. On the other hand, transcranial magnetic stimulation (TMS) and positron emission tomography (PET) are ranked at the bottom because of their poor resolutions and lower willingness of participants. Originality/value This paper proposes a common weight data envelopment analysis (DEA)-based decision model to cope with heterogeneous information collected by the experts to determine the best performing neuromarketing technology. The decision procedure enables the decision-makers to handle the problems of loss of information and multi-granularity by using the fusion of 2-tuple linguistic representation model and fuzzy information. Moreover, a DEA-based common weight model does not require subjective experts’ opinions to weight the evaluation criteria.

Evaluation of Comprehensive Cultivation Model of Undergraduate and Master Based on 2-tuple Linguistic Information

Evaluation of Comprehensive Cultivation Model of Undergraduate and Master Based on 2-tuple Linguistic Information

Evaluation on water resources and water ecological security with 2-tuple linguistic information

China is one of the countries who face the most serious contradiction between water supply and demand. In the meantime, there is a serious water pollution problem. The effective use and pollution control of water resources are the key to solve these problems. The industry supports the national econ omic development and is also the main user of the water resource. In 2014, the industrial water use accounted for 24% of China’s total, which was 20.71% in 1998. The industry is the main source of water pollution at the same time. Therefore, in a condition that the industrial economy develops positively, it is necessary to perform water-saving management and sewage control to promote rational allocation of water resources and sewage treatment technology. The key solution to these works are to increase green total-factor water efficiency. Hence, industrial green total-factor water efficiency has great research value. In this paper, we investigate the multiple attribute decision making (MADM) problems with 2-tuple linguistic information. We used the 2-tuple linguistic weighted Bonferroni mean (2TLWBM) operator to develop a procedure for multiple attribute decision making under the 2-tuple linguistic environments. Finally, a practical example for evaluating the water resources and water ecological security is given to verify the developed approach and to demonstrate its practicality and effectiveness.

Hesitant 2-tuple linguistic Bonferroni operators and their utilization in group decision making

Hesitant 2-tuple linguistic variable realizes a graded information approach to characterize the uncertainty of human cognition. This study is concerned with the development of new aggregation operators and aims to design a new group decision making approach to address the information fusion involving the interrelationship between aggregated terms and the prioritization relationship among decision makers under hesitant 2-tuple linguistic situation. Firstly, hesitant 2-tuple linguistic Bonferroni mean (H2TLBM) operator and prioritized weighted hesitant 2-tuple linguistic Bonferroni mean (PWH2TLBM) operator are established. Subsequently, some pertinent properties and special forms of the developed operators are studied in detail. To employ the proposed operators to solve group decision making problems, a novel TODIM (an acronym in Portuguese of interactive and multiple attribute decision making) method based on possibility degree is developed under the situation of hesitant 2-tuple linguistic information. The designed decision making method not only inherits the merits of the traditional TODIM approach, but also characterizes the interrelationship of criteria. The detailed process of solving problems is exemplified to highlight the practicality and feasibility of the designed method. Furthermore, comparative analysis with other methods is carried out to further offer insights on the designed decision method.

Models for MADM With 2-Tuple Linguistic Neutrosophic Dombi Bonferroni Mean Operators

The Dombi t-norm and Dombi t-conorm operations, which have the advantages of describing decision making information flexibly by using the general parameter, can be valid to deal with actual multiple attribute decision making (MADM) problems. Motivated by the basic Bonferroni mean (BM) operator, some novel Dombi Bonferroni mean (DBM) operators and Dombi geometric Bonferroni mean (DGBM) operators are developed to aggregate 2-tuple linguistic neutrosophic information in our manuscript. Obviously, some precious properties and numerical examples are given to testify the effective and scientific of these operators. Finally, the green supplier selection in green supply chain management is taken as an example to verify the proposed methods.

Model for Multiple Attribute Decision Making Based on Picture 2-Tuple Linguistic Power Aggregation Operators

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.

Interval-Valued $q$ -Rung Orthopair 2-Tuple Linguistic Aggregation Operators and Their Applications to Decision Making Process

The objective of this manuscript is to present the concept of interval-valued $q$ -rung orthopair 2-tuple linguistic set (IVq-RO2TLSs) and their basic operations. As a generalization of the sets, interval-valued q-rung orthopair fuzzy set is a more profitable way to express the uncertainties in the data while 2-tuple linguistic set deals with the qualitative aspects of the information. By utilizing both these features, we propose a concept of IVq-RO2TLSs and studies their properties. For it, firstly, we define the basic operational laws between the pairs of the sets and define the score, accuracy and basic operations. Secondly, based on the operational laws, we develop some weighted averaging and geometric aggregation operators for IVq-RO2TLSs and characterize their desirable properties. Thirdly, a novel approach is developed to solve multi-attribute decision making (MADM) problem with interval-valued q-rung orthopair 2-tuple linguistic information. Finally, several numerical examples are provided with some comparative study to validate the approach.

Diminishing Choquet Hesitant 2-Tuple Linguistic Aggregation Operator for Multiple Attributes Group Decision Making

In this article, we develop a diminishing hesitant 2-tuple averaging operator (DH2TA) for hesitant 2-tuple linguistic arguments. DH2TA work in the way that it aggregate all hesitant 2-tuple linguistic elements and during the aggregation process it also controls the hesitation in translation of the resultant aggregated linguistic term. We develop a scalar product for hesitant 2-tuple linguistic elements and based on the scalar product a weighted diminishing hesitant 2-tuple averaging operator (DWH2TA) is introduced. Moreover, combining Choquet integral with hesitant 2-tuple linguistic information, the diminishing Chouqet hesitant 2-tuple average operator (DCH2TA) is defined. The proposed operators higher reflect the correlations among the elements. After investigating the properties of these operators, a multiple attribute decision making method based on DCH2TA operator is proposed. Finally, an example is given to illustrate the significance and usefulness of proposed method.

Site Selection of Waste-to-Energy (WtE) Plant considering Public Satisfaction by an Extended VIKOR Method

Site selection of waste-to-energy (WtE) plant is critically important in the whole life cycle. Some research has been launched in the WtE plant site selection, but there is still a serious problem called Not In My Back Yard (NIMBY) effect that needs to be solved. To solve the problem, an improved multigroup VIKOR method is proposed to choose the optimal site and compromised sites. In the proposed method, the public satisfaction is fully considered where the public is invited as an evaluation group far more than creating general indicators to represent the public acceptance. First of all, an elaborate criteria system is built to evaluate site options comprehensively and the weights of criteria are identified by Analytic Hierarchy Process (AHP) method. Then, the interval 2-tuple linguistic information is adopted to assess the ratings for the established criteria. The interval 2-tuple linguistic ordered weighted averaging (ITL-OWA) operator is utilized to aggregate the opinions of evaluation committee while the opinions of the public are aggregated using weighted average operator. Finally, a case from south China which shows the computational procedure and the effectiveness of the proposed method is proved. Last but not least, a sensitivity analysis is conducted by comparing the results with different weights of evaluation group assessments.

MAGDM Method with Pythagorean 2-Tuple Linguistic Information and Applications in the HSE Performance Assessment of Laboratory

There is a significant gap between the safety management in the Chinese colleges and many renowned colleges in other countries. The subject of this study is how to assess the performance of health, safety, and environment (HSE) in Chinese college laboratories. The assessment system is established by three parts. First of all, HSE performance assessment indicators for laboratories in Chinese colleges are identified based on the previous studies. Then set valued iteration is used to calculate the weights of the various indicators. Following that, multiple attribute group decision-making (MAGDM) method with Pythagorean 2-tuple linguistic operators is used to assess the laboratory HSE performance in colleges. Finally, taking a college in Sichuan Province as an example, the proposed method is used to assess the laboratory HSE performance. The assessment result shows that the proposed method used in this study is practical and feasible.

A hybrid outranking method for greenhouse gas emissions’ institution selection with picture 2-tuple linguistic information

An appropriate greenhouse gas (GHG) emissions’ institution largely affects long-term development of cement corporates. The primary objective of this paper is to investigate a scientific method for selecting an optimal institution for a cement corporate. The paper mainly makes the following contributions to effectively resolving this selection problem. Given the capacity of picture 2-tuple linguistic sets (P2TLSs) in depicting voting information, they are used as evaluation representation in this case. Another contribution is that this paper newly proposes a prospect theory-based score function to rank picture 2-tuple linguistic numbers (P2TLNs). The proposed score function effectively overcomes the limitations in the existing score function by considering the voting potential of those decision-makers (DMs) who hold “abstain” opinion. Meanwhile, this proposed score function also adequately considers the rational-bounded behavior of DMs, thereby making the evaluation more approximate to the reality. Furthermore, this paper investigates a hybrid outranking method to select institution in the context of P2TLSs. It takes different types of preference functions and the Elimination and Choice Translating Reality (ELECTRE) method into account simultaneously. Compared with other similar type methods, this hybrid method can flexibly choose criteria type and provide specific values to represent quantitative dominance relation rather than qualitative judgment. Finally, an illustrative example and comparative analyses are provided to certify the availability and reliability of the proposed method.

An outranking approach for hesitant 2-tuple linguistic sets

The hesitant 2-tuple linguistic set (H2TLS), a special case of hesitant 2-tuple linguistic representation model, not only can express the qualitative preferences of the decision makers (DMs), but can effectively reflect their uncertainty and hesitancy with the help of translation parameter containing more than one element assigned to each linguistic variable of the linguistic term set (LTS). This paper develops an outranking method to address the solution to multi-criteria group decision-making (MCGDM) problems in the context of hesitant 2-tuple linguistic information. The main contribution of this paper is twofold. One is to propose the outranking relations of H2TLEs based on the proposed directional Hausdorff distance. Another is to establish an outranking method, similar to the ELECTRE method, to solve MCGDM problems in which attributes are evaluated by hesitant 2-tuple linguistic arguments under certain criteria. Last but not the least, a numerical example and a comparison analysis of the results obtained both in the proposed method and fuzzy TOPSIS (Technique for order preference by similarity to ideal solution) method for H2TLSs based on the generalized distance measure are conducted to verify the practicality and effectiveness of the work.

A multi criteria comprehensive evaluation approach for emergency response capacity with interval 2-tuple linguistic information

Emergency response capacity evaluation (ERCE) is an important and challenging issue in emergency management with the frequent occurrence of emergency events. Because of their different backgrounds and preferences, decision makers (DMs) often prefer to use linguistic variables from different linguistic term sets to express their decision information about the importance and the ratings of multi criteria involved in ERCE issue, some of which may be imprecise and uncertain. Therefore, this paper proposes a multi criteria comprehensive evaluation (MCCE) approach for ERCE with interval 2-tuple linguistic information. First, a new method for comparison between interval 2-tuples is proposed. Then, the classic analytical hierarchy process is extended into the ITL-AHP, in which the interval 2-tuple linguistic preference relation (ITLPR) and its multiplicative consistency are defined. An iterative algorithm to improve the consistency level of an ITLPR is proposed. Based on improved ITLPRs, the priority weights of criteria are derived by the normalizing rank summation method. In individual decision information collecting processes, both subjective weights and objective weights of DMs are considered. Furthermore, some interval 2-tuple interval weighted aggregation operators in which the weight vectors take the form of interval 2-tuple linguistic information are developed. Finally, a numerical illustration and comparison analyses are provided to elucidate the feasibility and superiority of the proposed method. The proposed method can provide a flexible way to perceive and appraise the emergency response capacity (REC) and an effective tool to handle the emergency management performance evaluation and decision making under fuzzy and uncertain information environment.

Outranking method for intuitionistic 2-tuple fuzzy linguistic information model in group decision making

This paper attempts to develop an outranking method based on intuitionistic 2-tuple fuzzy linguistic information and apply it to multi-criteria group decision-making problems. The theory of intuitionistic 2-tuple fuzzy linguistic elements (I2FLEs) is useful for modeling impressions and quantifying the ambiguous nature of subjective judgments in a convenient manner. The family of ELECTRE methods is well known and widely used outranking method, but it has not been investigated within the intuitionistic 2-tuple fuzzy linguistic environment. ELECTRE uses the concept of an outranking relationship. Therefore, the directional Hausdorff distance, which uses I2FLEs, is proposed and the outranking relations are subsequently defined using this distance. Furthermore, using the proposed score and accuracy functions of I2FLEs, this paper also develops an outranking method based on intuitionistic fuzzy support function, intuitionistic fuzzy risk function, intuitionistic fuzzy credibility function, and the net outranking flow index similar to the PROMETHEE method. An illustrative example is given to demonstrate the practicality and effectiveness of the developed approaches. Finally, a comparative discussion of two decision-making methods is conducted to demonstrate the advantages of the proposed method over the other.

Matrix games with 2-tuple linguistic information

In this contribution, a two-player constant-sum 2-tuple linguistic matrix game is described, and a linguistic linear programming (LLP) approach is proposed to solve this class of games. The proposed approach can be perceived as a unified mechanism in the sense that it can be adopted to solve linguistic matrix game problems, LLP problems, and linguistic multi-attribute decision-making (MADM) problems. The latter is exhibited by presenting examples of linguistic MADM problems modeled as two-player constant-sum linguistic matrix games with Nature as the second player.

Models for Green Supplier Selection in Green Supply Chain Management With Pythagorean 2-Tuple Linguistic Information

In recent years, the environmental problems in China have become more and more serious, for example, resource depletion, environmental pollution, ecological imbalance, and so on. At the same time, the laws and regulations about the environmental protection in the world are constantly introduced, the academic research about the environmental issues is also increasing, more and more consumers show concern for the green products, and the restrictions of the “green trade barrier” in the international to the export products in China enterprises must pay attention to the influence of their behavior on the environment in pursuit of economic efficiency. In this context, the green supply chain management (GSCM) emerges. GSCM theory first appeared in some foreign countries, and started later in China. Compared with some developed countries, the GSCM theory in China is still not mature. From the source speaking, there is lack of a complete GSCM system. In this paper, we combine the generalized weighted Bonferroni mean (GWBM) operator, generalized weighted geometric Bonferroni mean (GWGBM) operator, dual GWBM operator, and dual GWGBM operator with Pythagorean 2-tuple linguistic numbers to propose the generalized Pythagorean 2-tuple linguistic WBM (GP2TLWBM) operator, generalized Pythagorean 2-tuple linguistic WGBM (GP2TLWGBM) operator, dual GP2TLWBM (DGP2TLWBM) operator, and dual GP2TLWGBM (DGP2TLWGBM) operator, and then, the multiple attribute decision-making (MADM) methods are developed based on DGP2TLWBM and DGP2TLWGBM operators. Finally, we use an example for green supplier selection to prove the MADM process of the proposed algorithms.

Some new Hamacher aggregation operators under single-valued neutrosophic 2-tuple linguistic environment and their applications to multi-attribute group decision making

Abstract This paper proposes an approach to linguistic multiple attribute group decision making (MAGDM) problem with single-valued neutrosophic 2-tuple linguistic (SVN2TL) assessment information by adding a subjective imprecise estimation of reliability of the 2-tuple linguistic terms (2TLTs). SVN2TL includes the truth-membership (TM), indeterminacy-membership (IM) and faulty-membership (FM), which can express the incomplete, indeterminate and inconsistent information perfectly and avoid information and precision losing in aggregation process ideally. We first propose the concept of SVN2TL set (SVN2TLS) and single valued neutrosophic 2-tuple linguistic element (SVN2TLE), basic operational rules on SVN2TLEs via Hamacher triangular norms, and ranking method for SVN2TLEs. Then, some SVN2TL aggregation operators including SVN2TL Hamacher weighted averaging (SVN2TLHWA) operator, SVN2TL Hamacher geometric weighted averaging (SVN2TLHGWA) operator, are developed, their some properties are investigated as well. Moreover, we apply new operators to develop approach to MAGDM problem with SVN2TL assessment information, where a model for optimal weighting vector is constructed. Finally, an numerical example related to evaluation of emergency response solutions for sustainable community development is provided to show the utility and effectiveness of the method described in this paper. A sensitivity and comparative analysis are also conducted to demonstrate the strength and practicality of the proposed method.

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.