An adjustable approach to multi-criteria group decision-making based on a preference relationship under fuzzy soft information

Group decision-making is a collaborative process to find optimal alternative based on an aggregation judgment. Various techniques have been suggested to solve decision-making problems; however, the rapid growth of uncertainties in industry and organizations highlights the application of fuzzy set theory and soft set theory in this area. In this regard, fuzzy soft model can be considered as an efficient tool in decision-making. To date, different algorithms have been proposed for solving collective decision-making problems based on fuzzy soft set theory. In order to reach the process of consensus, the existing methods have mostly used the t-norms, such as “AND” operator which can be successfully applied to individual decision-making problems including multi-source datasets. However, such approaches fail to consider multi-observer problems in group decision-making processes. Additionally, in the selection step, the existing methods lack a comprehensive priority approach; they focus on a hierarchical preference which ignores incomparable alternatives. To overcome these issues, this paper proposes an adjustable multi-criteria group decision-making approach based on a preference relationship of fuzzy soft sets. First, we construct two topological spaces over the set of objects, and then, develop a preference relationship of objects by using open sets of these two topologies. A multi-phase method is then designed to rank objects in multi-criteria group decision-making problems based on such preference relationship. We also extend the proposed algorithm to weighted case in order to have a higher level of adaptability with real-world problems. Dataset from “www.booking.com” Web site is applied to show the capability of this new method in comparison with results from the well-known literature approaches

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

New Challenges in Neutrosophic Theory and Applications

Neutrosophic theory has representatives on all continents and, therefore, it can be said to be a universal theory. On the other hand, according to the three volumes of “The Encyclopedia of Neutrosophic Researchers” (2016, 2018, 2019), plus numerous others not yet included in Encyclopedia book series, about 1200 researchers from 73 countries have applied both the neutrosophic theory and method. Neutrosophic theory was founded by Professor Florentin Smarandache in 1998; it constitutes further generalization of fuzzy and intuitionistic fuzzy theories. The key distinction between the neutrosophic set/logic and other types of sets/logics lies in the introduction of the degree of indeterminacy/neutrality (I) as an independent component in the neutrosophic set. Thus, neutrosophic theory involves the degree of membership-truth (T), the degree of indeterminacy (I), and the degree of non-membership-falsehood (F). In recent years, the field of neutrosophic set, logic, measure, probability and statistics, precalculus and calculus, etc., and their applications in multiple fields have been extended and applied in various fields, such as communication, management, and information technology. We believe that this book serves as useful guidance for learning about the current progress in neutrosophic theories. In total, 22 studies have been presented and reflect the call of the thematic vision. The contents of each study included in the volume are briefly described as follows. The first contribution, authored by Wadei Al-Omeri and Saeid Jafari, addresses the concept of generalized neutrosophic pre-closed sets and generalized neutrosophic pre-open sets in neutrosophic topological spaces. In the article “Design of Fuzzy Sampling Plan Using the Birnbaum-Saunders Distribution”, the authors Muhammad Zahir Khan, Muhammad Farid Khan, Muhammad Aslam, and Abdur Razzaque Mughal discuss the use of probability distribution function of Birnbaum–Saunders distribution as a proportion of defective items and the acceptance probability in a fuzzy environment. Further, the authors Derya Bakbak, Vakkas Uluc¸ay, and Memet S¸ahin present the “Neutrosophic Soft Expert Multiset and Their Application to Multiple Criteria Decision Making” together with several operations defined for them and their important algebraic properties. In “Neutrosophic Multigroups and Applications”, Vakkas Uluc¸ay and Memet S¸ahin propose an algebraic structure on neutrosophic multisets called neutrosophic multigroups, deriving their basic properties and giving some applications to group theory. Changxing Fan, Jun Ye, Sheng Feng, En Fan, and Keli Hu introduce the “Multi-Criteria Decision-Making Method Using Heronian Mean Operators under a Bipolar Neutrosophic Environment” and test the effectiveness of their new methods. Another decision-making study upon an everyday life issue which empowered us to organize the key objective of the industry developing is given in “Neutrosophic Cubic Einstein Hybrid Geometric Aggregation Operators with Application in Prioritization Using Multiple Attribute Decision-Making Method” written by Khaleed Alhazaymeh, Muhammad Gulistan, Majid Khan, and Seifedine Kadry

Subjective stakeholder dynamics relationships treatment: a methodological approach using fuzzy decision-making

Since the stakeholder theory was proposed to explain the interaction among its agents, extensive approaches have been developed. However, the literature continues to suggest the development of new methodologies that allow an analysis of the dynamics and uncertainty of the relationships between each agent. In this sense, this research proposes a novel methodology for the treatment of subjective stakeholder dynamics using fuzzy decision-making. The study proposes a mathematical methodological perspective for the treatment of subjective relationships among stakeholders, which allows a predictive simulation tool to be developed for attitude and personal preferences to analyze the links among all stakeholders. (...

Two-Step Many-Objective Optimal Power Flow Based on Knee Point-Driven Evolutionary Algorithm

To coordinate the economy, security and environment protection in the power system operation, a two-step many-objective optimal power flow (MaOPF) solution method is proposed. In step 1, it is the first time that knee point-driven evolutionary algorithm (KnEA) is introduced to address the MaOPF problem, and thereby the Pareto-optimal solutions can be obtained. In step 2, an integrated decision analysis technique is utilized to provide decision makers with decision supports by combining fuzzy c-means (FCM) clustering and grey relational projection (GRP) method together. In this way, the best compromise solutions (BCSs) that represent decision makers' different, even conflicting, preferences can be automatically determined from the set of Pareto-optimal solutions. The primary contribution of the proposal is the innovative application of many-objective optimization together with decision analysis for addressing MaOPF problems. Through examining the two-step method via the IEEE 118-bus system and the real-world Hebei provincial power system, it is verified that our approach is suitable for addressing the MaOPF problem of power systems.Comment: Accepted by Journal Processe

Financial crises and bank failures: a review of prediction methods

In this article we analyze financial and economic circumstances associated with the U.S. subprime mortgage crisis and the global financial turmoil that has led to severe crises in many countries. We suggest that the level of cross-border holdings of long-term securities between the United States and the rest of the world may indicate a direct link between the turmoil in the securitized market originated in the United States and that in other countries. We provide a summary of empirical results obtained in several Economics and Operations Research papers that attempt to explain, predict, or suggest remedies for financial crises or banking defaults; we also extensively outline the methodologies used in them. The intent of this article is to promote future empirical research for preventing financial crises.Subprime mortgage ; Financial crises

Studies on Product Design using Ergonomic Considerations

Embedding ergonomic consideration into product/machine/equipment/component design as well as work environment taking into account both psychological and physical needs of user helps to enhance user efficiency, satisfaction and productivity. It is vital to find best design elements to visualize the product which possesses the characteristics not only to satisfy the users but also reduces fatigue and injury during prolonged use. Although subjective and objective product characteristics are important during product design, user comfort becomes a vital factor that can be quantified by the analysis on continuous physical interaction between product and user. Beside above influential factors, ergonomic design of product also considers cognitive and behavioral information during the design stage with a view to improve the comfort level of the user and aesthetic look of the product. To address above issues, an integrated approach using statistical and artificial intelligence techniques has been proposed in this thesis to effectively handle subjective and objectives characteristics during design phase. The statistical method is used to assess various user requirements and their significance whereas artificial intelligence method determines the relationship between user requirements and product characteristics. Since most of the psychological needs of users are difficult to express quantitatively, combined approach of statistical and artificial intelligence method can handle the subjectivity and uncertainty in an effective manner. The approach has been demonstrated with the help of design of office chair. Keeping view with the physical interaction between human soft tissue and product as a measuring factor of comfort sensation in an office environment, a numerical analysis of human soft tissue-chair seat model has been introduced into current work. In order to evaluate superior ergonomically designed product (office chair), suitable multi-attribute decision making (MADM) approach based on few important features has been chosen to address the usability of product improving satisfaction level of customer. The study also analyses a kinematic model of human upper arm extremity to diagnose comfort arm posture that allows the operator to have a comfort work zone within which possible postures can be accepted

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