Distributed Linguistic Representations in Decision Making: Taxonomy, Key Elements and Applications, and Challenges in Data Science and Explainable Artificial Intelligence

Distributed linguistic representations are powerful tools for modelling the uncertainty and complexity of preference information in linguistic decision making. To provide a comprehensive perspective on the development of distributed linguistic representations in decision making, we present the taxonomy of existing distributed linguistic representations. Then, we review the key elements and applications of distributed linguistic information processing in decision making, including the distance measurement, aggregation methods, distributed linguistic preference relations, and distributed linguistic multiple attribute decision making models. Next, we provide a discussion on ongoing challenges and future research directions from the perspective of data science and explainable artificial intelligence.National Natural Science Foundation of China (NSFC) 71971039 71421001,71910107002,71771037,71874023 71871149Sichuan University sksyl201705 2018hhs-5

Development of group decision making model under fuzzy environment

Multi criteria group decision making (MCGDM) methods are broadly used in the real-world decision circumstances for homogeneous groups. Some decision-makers’viewpoints at times are more important or reliable than others, or they may differ in terms of the decision-maker experience, education, expertise and other aspects. Thus, a heterogeneous group of decision makers with dissimilar members has to be composed in MCGDM. Multi-dimensional personnel evaluation is one of the most critical decisions to make in order to achieve the organization goals. In many situations, raters may decide on the basis of imprecise information coming from a variety of sources about ratee with respect to criteria. In fact, some criteria are completely quantifiable, some partially quantifiable, and others completely subjective; moreover crisp data is inappropriate to model real-world circumstances. Linguistic labels or fuzzy preferences are therefore, used to deal with uncertain and inaccurate factors involved and seem more reliable in complex group decision situations. In this research, heterogeneous group decision making models under fuzzy environment for multi-dimensional personnel evaluation were proposed to compensate the differences of decision makers’ knowledge such as: education,expertise, experience and other aspects. A new fuzzy group decision making method was developed under the linguistic framework for heterogeneous group decision making that aims at a desired consensus. The method allocates different weights for each decision maker using linguistic terms to express their fuzzy preferences for alternative solutions and for individual judgments. Besides, the classical ordinal approach method under a linguistic framework is developed for heterogeneous group decision making, which allows group members to express their fuzzy preferences in linguistic terms for alternative selection and for individual judgments. Furthermore, a fuzzy extension of technique for order preference by similarity to ideal solution (TOPSIS) method under fuzzy environment was proposed. The method covers heterogeneous group decision making by considering the decision makers’ viewpoint weights. In order to solve the problem of discrepancy between decision making methods’ results, a new optimization method was developed, to aggregate the results’of different decision making models. The four proposed methods were used in a case study. Proposed methods focused on the implementation of fuzzy logic approach in the personnel evaluation system. Furthemore, personnel were evaluated from different points of view (supervisors,colleagues, inferiors and employee him/herself). A fuzzy Delphi method and linguistic terms represented by the fuzzy numbers were developed to elicit qualitative and quantitative criteria and assess criteria weights and relative importance of evaluation group’s viewpoints. Then, the proposed methods’ results were compared to already established methods. The study identified that the results of the proposed methods are closely related to other methods and the selections made by the proposed methods approximately are identical with the other already established methods. The Spearman’s rank correlation coefficient shows highly consistent rankings obtained by the methods. No significant difference in the ranking of the proposed methods and the other established methods was observed. The results of the problems solution based on the aggregated proposed model show that the aggregated model achieved the highest value in the Spearman’s rank correlation compared to the average method and Copeland function. Furthermore, the high Spearman’s rank correlation coefficient between the rankings supports the consistency of the results and similarity of applicability of the methods

Assessment of Sustainable Development

The objective of this paper is to introduce fuzzy set theory and develop fuzzy mathematical models to assess sustainable development based on context-dependent economic, ecological, and societal sustainability indicators. Membership functions are at the core of fuzzy models, and define the degree to which indicators contribute to development. Although a decision-making process regarding sustainable development is subjective, fuzzy set theory links human expectations about development, expressed in linguistic propositions, to numerical data, expressed in measurements of sustainability indicators. In the future, practical implementation of such models will be based on elicitation of expert knowledge to construct a membership function. The fuzzy models developed in this paper provide a novel approach to support decisions regarding sustainable development.agriculture;assessment;fuzzy set theory;sustainable development

Dynamic reference point method with probabilistic linguistic information based on the regret theory for public health emergency decision-making

Group emergency decision-making is an uncertain and dynamic process, in which the decision makers may be bounded rational and have a risk appetite. To depict the vague qualitative assessments, the probabilistic linguistic term sets are employed to express the perceptions of decision makers. First, considering the regret-aversion of the decision makers’ psychological characteristic, the value function and the regret-rejoice function in the regret theory are modified to adapt the probabilistic linguistic information. Second, the definition and aggregation operators of the probabilistic linguistic time variable are proposed to describe and aggregate the dynamic decision information. Third, the probabilistic linguistic models based on the dynamic reference point method and the regret theory are studied to maximise the expectation-levels of alternatives at the relative time point. The proposed method is applied to select the optimal response strategy for the outbreak of COVID-19 in China. Finally, the comparative analysis is designed to verify the applicability and reasonability of the proposed method

A Novel Approach for the Selection of Power-Generation Technology Using a Linguistic Neutrosophic CODAS Method: A Case Study in Libya

Rapid increases in energy demand and international drive to reduce carbon emissions from fossil fuels have led many oil-rich countries to diversify their energy portfolio and resources. Libya is one of these countries, and it has recently become interested in utilizing its renewable-energy resources in order to reduce financial and energy dependency on oil reserves. This paper introduces an original multicriteria decision-making Pairwise-CODAS model in which the modification of the CODAS method was made using Linguistic Neutrosophic Numbers (LNN). The paper also suggests a new LNN Pairwise (LNN PW) model for determining the weight coefficients of the criteria developed by the authors. By integrating these models with linguistic neutrosophic numbers, it was shown that it is possible to a significant extent to eliminate subjective qualitative assessments and assumptions by decision makers in complex decision-making conditions. The LNN PW-CODAS model was tested and validated in a case study of the selection of optimal Power-Generation Technology (PGT) in Libya. Testing of the model showed that the proposed model based on linguistic neutrosophic numbers provides objective expert evaluation by eliminating subjective assessments when determining the numerical values of criteria. A sensitivity analysis of the LNN PW-CODAS model, carried out through 68 scenarios of changes in the weight coefficients, showed a high degree of stability of the solutions obtained in the ranking of the alternatives. The results were validated by comparison with LNN extensions of four multicriteria decision-making models

CODAS methods for multiple attribute group decision making with interval-valued bipolar uncertain linguistic information and their application to risk assessment of Chinese enterprises’ overseas mergers and acquisitions

Bipolar fuzzy set theory has been successfully applied in some areas, but there are situations in real life which can’t be represented by bipolar fuzzy sets. However, all the existing approaches are unsuitable to describe the positive and negative membership degree an element to an uncertain linguistic label to have an interval value, which can reflect the decision maker’s confidence level when they are making an evaluation. In order to overcome this limit, we propose the definition of interval-valued bipolar uncertain linguistic sets (IVBULSs) to solve this problem based on the bipolar fuzzy sets and uncertain linguistic information processing models. In this paper, we extend the traditional information aggregating operators to interval-valued bipolar uncertain linguistic sets (IVBULSs) and propose some IVBUL aggregating operators. Then, we extend the CODAS method to solve multiple attribute group decision making (MAGDM) issues with interval-valued bipolar uncertain linguistic numbers (IVBULNs) based on these operators. An example for risk assessment of Chinese enterprises’ overseas mergers and acquisitions (M&As) is given to illustrate the proposed methodology