115 research outputs found

    A Method Based on Intuitionistic Fuzzy Dependent Aggregation Operators for Supplier Selection

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    Recently, resolving the decision making problem of evaluation and ranking the potential suppliers have become as a key strategic factor for business firms. In this paper, two new intuitionistic fuzzy aggregation operators are developed: dependent intuitionistic fuzzy ordered weighed averaging (DIFOWA) operator and dependent intuitionistic fuzzy hybrid weighed aggregation (DIFHWA) operator. Some of their main properties are studied. A method based on the DIFHWA operator for intuitionistic fuzzy multiple attribute decision making is presented. Finally, an illustrative example concerning supplier selection is given

    Power of Continuous Triangular Norms with Application to Intuitionistic Fuzzy Information Aggregation

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    The paper aims to investigate the power operation of continuous triangular norms (t-norms) and develop some intuitionistic fuzzy information aggregation methods. It is proved that a continuous t-norm is power stable if and only if every point is a power stable point, and if and only if it is the minimum t-norm, or it is strict, or it is an ordinal sum of strict t-norms. Moreover, the representation theorem of continuous t-norms is used to obtain the computational formula for the power of continuous t-norms. Based on the power operation of t-norms, four fundamental operations induced by a continuous t-norm for the intuitionistic fuzzy (IF) sets are introduced. Furthermore, various aggregation operators, namely the IF weighted average (IFWA), IF weighted geometric (IFWG), and IF mean weighted average and geometric (IFMWAG) operators, are defined, and their properties are analyzed. Finally, a new decision-making algorithm is designed based on the IFMWAG operator, which can remove the hindrance of indiscernibility on the boundaries of some classical aggregation operators. The practical applicability, comparative analysis, and advantages of the study with other decision-making methods are furnished to ascertain the efficacy of the designed method

    Multiattribute group decision-making approach with linguistic Pythagorean fuzzy information

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    Novel possibility spherical fuzzy soft set model and its application for a decision making

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    We talk about possibility spherical fuzzy soft set (shortly PSFS set) has much stronger ability than possibility Pythagorean fuzzy soft set (shortly PPFS set) and intuitionistic fuzzy soft set. The PSFS soft set is a generalization of PPFS set and soft set. Here we talk through some operations consisting of complement, union, intersection, AND and OR. We verify that the De Morgan’s laws, associate laws and distributive laws are satisfied in the case of PSFS sets. Also we discuss comparative analysis for the soft set model under the scheme of PSFS sets. Finally, an illustrative example is mentioned for the soft set model using PSFS set.Publisher's Versio

    COMPLEX INTUITIONISTIC FUZZY DOMBI PRIORITIZED AGGREGATION OPERATORS AND THEIR APPLICATION FOR RESILIENT GREEN SUPPLIER SELECTION

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    One of the main problems faced by resilient supply chain management is how to solve the problem of supplier selection, which is a typical multi-attribute decision-making (MADM) problem. Given the complexity of the current decision-making environment, the primary influence of this paper is to propose the theory of Dombi operational laws based on complex intuitionistic fuzzy (CIF) information. Moreover, we examined the theory of CIF Dombi prioritized averaging (CIFDPA) and CIF weighted Dombi prioritized averaging (CIFWDPA), where these operators are the modified version of the prioritized aggregation operators and Dombi aggregation operators for fuzzy, intuitionistic fuzzy, complex fuzzy and complex intuitionistic fuzzy information. Some reliable properties for the above operators are also established. Furthermore, to state the art of the proposed operators, an application example in the presence of the invented operators is evaluated for managing resilient green supplier selection problems. Finally, through comparative analysis with mainstream technologies, we provide some mechanism explanations for the proposed method to show the supremacy and worth of the invented theory

    Interval-Valued Intuitionistic Fuzzy Einstein Geometric Choquet Integral Operator and Its Application to Multiattribute Group Decision-Making

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    With respect to the multiattribute decision-making (MADM) problem in which the attributes have interdependent or interactive phenomena under the interval-valued intuitionistic fuzzy environment, we propose a group decision-making approach based on the interval-valued intuitionistic fuzzy Einstein geometric Choquet integral operator (IVIFEGC). Firstly, the Einstein operational laws and some basic principle on interval-valued intuitionistic fuzzy sets are introduced. Then, the IVIFEGC is developed and some desirable properties of the operator are studied. Further, an approach to multiattribute group decision-making with interval-valued intuitionistic fuzzy information is developed, where the attributes have interdependent phenomena. Finally, an illustrative example is used to illustrate the developed approach

    Notes on soft sets and aggregation operators

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    [EN]Under uncertainty, traditional sets may not be sufficient to represent real-world phenomena, and fuzzy sets can provide a more flexible and natural approach. The concept of fuzzy sets has been widely used in various fields, including artificial intelligence, control theory, decision-making, and pattern recognition. Fuzzy sets can also be combined with other mathematical tools, such as probability theory, to provide a more comprehensive approach to uncertainty management. In these notes, we explore the concept of fuzzy sets under uncertainty, and their applications in various fields. We discuss the fundamental concepts of fuzzy sets, including fuzzy membership functions, fuzzy operations, and fuzzy relations. We also examine different types of uncertainty, including epistemic and aleatory uncertainty, and how fuzzy sets can be used to model and manage uncertainty in these cases
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