Necessary and possible hesitant fuzzy sets: A novel model for group decision making

We propose an extension of Torra’s notion of hesitant fuzzy set, which appears to be well suited to group decision making. In our model, indecisiveness in judgements is described by two nested hesitant fuzzy sets: the smaller, called necessary, collects membership values determined according to a rigid evaluation, whereas the larger, called possible, comprises socially acceptable membership values. We provide several instances of application of our methodology, and accordingly design suitable individual and group decision procedures. This novel approach displays structural similarities with Atanassov’s intuitionistic fuzzy set theory, but has rather different goals. Our source of inspiration comes from preference theory, where a bi-preference approach has proven to be a useful extension of the classical mono-preference modelization in the fields of decision theory and operations research

Teranga Go!: Carpooling Collaborative Consumption Community with multi-criteria hesitant fuzzy linguistic term set opinions to build confidence and trust

La Comisión Europea da prioridad al fomento del consumo colaborativo en consonancia con la visión de la Estrategia Europa 2020 para un crecimiento inteligente, sostenible e integrador. En respuesta, se ha desarrollado una comunidad en línea dedicada al consumo colaborativo llamada Teranga Go!, centrada en la comunidad senegalesa que viaja en coche de Europa a África. Las relaciones de viaje compartido dentro de Teranga Go! hacen hincapié en un auténtico sentido de comunidad, interacciones sociales entre los usuarios y conexiones tecnológicas, con la confianza como elemento crucial. Para aumentar la confianza y la seguridad entre los miembros de Teranga Go! se ha implantado un sistema inteligente de apoyo a la toma de decisiones basado en la computación con palabras. En este sistema, los participantes actúan como expertos, evaluando las aptitudes del conductor y asignando colectivamente un valor lingüístico, denominado "karma", que representa la opinión colectiva de las personas que han viajado con el conductor. Este karma se muestra públicamente en los perfiles de los usuarios, y para representar las opiniones de los expertos en el proceso de evaluación se utiliza un modelo de toma de decisiones multicriterio multiexperto que emplea términos lingüísticos difusos vacilantes.The European Commission prioritizes promoting collaborative consumption in alignment with the Europe 2020 Strategy's vision for smart, sustainable, and inclusive growth. In response, a dedicated online community called Teranga Go! has been developed for collaborative consumption, focusing on the Senegalese community traveling by car from Europe to Africa. Carpooling relationships within Teranga Go! emphasize a genuine sense of community, social interactions among users, and technological connections, with trust as a crucial element. To enhance confidence, trust, and safety among Teranga Go! members, an intelligent decision support system based on computing with words has been implemented. In this system, participants act as experts, assessing driver aptitudes and collectively assigning a linguistic value, referred to as "karma," which represents the collective opinion of individuals who have traveled with the driver. This karma is publicly displayed on user profiles, and a Multi-Expert Multi-Criteria Decision Making model, employing Hesitant Fuzzy Linguistic Terms, is utilized to represent expert opinions in the evaluation process.Instituto Interuniversitario de Investigación en Data Science and Computational Intelligence (DaSCI

Interval-valued 2-tuple hesitant fuzzy linguistic term set and its application in multiple attribute decision making

[EN] The hesitant fuzzy linguistic term sets can retain the completeness of linguistic information elicitation by assigning a set of possible linguistic terms to a qualitative variable. However, sometimes experts cannot make sure that the objects attain these possible linguistic terms but only provide the degrees of confidence to express their hesitant cognition. Given that the interval numbers can denote the possible membership degrees that an object belongs to a set, it is suitable and convenient to provide an interval-valued index to measure the degree of a linguistic variable to a given hesitant fuzzy linguistic term set. Inspired by this idea, we introduce the concept of interval-valued 2-tuple hesitant fuzzy linguistic term set (IV2THFLTS) based on the interval number and the hesitant fuzzy linguistic term set. Then, we define some interval-valued 2-tuple hesitant fuzzy linguistic aggregation operators. Afterwards, to overcome the instability of subjective weights, we propose a method to compute the weights of attributes. For the convenience of application, a method is given to solve the multiple attribute decision making problems with IV2THFLTSs. Finally, a case study is carried out to validate the proposed method, and some comparisons with other methods are given to show the advantages of the proposed method.The work was supported in part by the National Natural Science Foundation of China (Nos. 71501135, 71771156), the China Postdoctoral Science Foundation (2016T90863, 2016M602698), the Fundamental Research Funds for the central Universities (No. YJ201535), and the Scientific Research Foundation for Excellent Young Scholars at Sichuan University (No. 2016SCU04A23).Si, G.; Liao, H.; Yu, D.; Llopis Albert, C. (2018). Interval-valued 2-tuple hesitant fuzzy linguistic term set and its application in multiple attribute decision making. Journal of Intelligent & Fuzzy Systems. 34(6):4225-4236. https://doi.org/10.3233/JIFS-171967S4225423634

A systematic literature review of soft set theory

[EN] Soft set theory, initially introduced through the seminal article ‘‘Soft set theory—First results’’ in 1999, has gained considerable attention in the field of mathematical modeling and decision-making. Despite its growing prominence, a comprehensive survey of soft set theory, encompassing its foundational concepts, developments, and applications, is notably absent in the existing literature. We aim to bridge this gap. This survey delves into the basic elements of the theory, including the notion of a soft set, the operations on soft sets, and their semantic interpretations. It describes various generalizations and modifications of soft set theory, such as N-soft sets, fuzzy soft sets, and bipolar soft sets, highlighting their specific characteristics. Furthermore, this work outlines the fundamentals of various extensions of mathematical structures from the perspective of soft set theory. Particularly, we present basic results of soft topology and other algebraic structures such as soft algebras and sigma-algebras. This article examines a selection of notable applications of soft set theory in different fields, including medicine and economics, underscoring its versatile nature. The survey concludes with a discussion on the challenges and future directions in soft set theory, emphasizing the need for further research to enhance its theoretical foundations and broaden its practical applications. Overall, this survey of soft set theory serves as a valuable resource for practitioners, researchers, and students interested in understanding and utilizing this flexible mathematical framework for tackling uncertainty in decision-making processes

Induced hesitant 2-tuple linguistic aggregation operators with application in group decision making

In this article, hesitant 2-tuple linguistic arguments are used to evaluate the group decision making problems which have inter dependent or inter active attributes. Operational laws are developed for hesitant 2-tuple linguistic elements and based on these operational laws hesitant 2- tuple weighted averaging operator and generalized hesitant 2- tuple averaging operator are proposed. Combining Choquet integral with hesitant 2-tuple linguistic information, some new aggregation operators are defined, including the hesitant 2-tuple correlated averaging operator, the hesitant 2-tuple correlated geometric operator and the generalized hesitant 2-tuple correlated averaging operator. These proposed operators successfully manage the correlations among the elements. After investigating the properties of these operators, a multiple attribute decision making method based on these operators, is suggested. Finally, an example is given to illustrate the practicality and feasibility of proposed method

Fuzzy Systems in Business Valuation

This research aims to develop a model that is able to integrate and objectify information provided by the different business valuation methods, incorporating quality management in its formal approach, which to date has not been considered in the literature about business valuation or quality management. Firstly, the company is valued using the methods which best adapt to its specific characteristics. Because of the subjectivity inherent in any valuation process, the results will be expressed through Triangular Fuzzy Numbers (TFN). These Fuzzy Numbers will be aggregated and summarized by applying Basic Defuzzification Distribution Uncertain Probabilistic Ordered Weighted Averaging operator (BADD-UPOWA). The weighting factors will be: the degree of confidence in each of the business valuation methods applied, and the innovative use of the company’s position on Crosby’s Quality Administration Grid. The results from application of the model in a case study show a significant reduction in uncertainty in contrast to the initial valuations. Moreover, the proposed methodology is seen to increase the final value of the company as its advances in quality management

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

Fuzzy Mathematics

This book provides a timely overview of topics in fuzzy mathematics. It lays the foundation for further research and applications in a broad range of areas. It contains break-through analysis on how results from the many variations and extensions of fuzzy set theory can be obtained from known results of traditional fuzzy set theory. The book contains not only theoretical results, but a wide range of applications in areas such as decision analysis, optimal allocation in possibilistics and mixed models, pattern classification, credibility measures, algorithms for modeling uncertain data, and numerical methods for solving fuzzy linear systems. The book offers an excellent reference for advanced undergraduate and graduate students in applied and theoretical fuzzy mathematics. Researchers and referees in fuzzy set theory will find the book to be of extreme value