82 research outputs found

    A novel method based on extended uncertain 2-tuple linguistic muirhead mean operators to MAGDM under uncertain 2-tuple linguistic environment

    Get PDF
    The present work is focused on multi-attribute group decision-making (MAGDM) problems with the uncertain 2-tuple linguistic information (ULI2–tuple) based on new aggregation operators which can capture interrelationships of attributes by a parameter vector P. To begin with, we present some new uncertain 2-tuple linguistic MM aggregation (UL2–tuple-MM) operators to handle MAGDM problems with ULI2–tuple, including the uncertain 2-tuple linguistic Muirhead mean (UL2–tuple-MM) operator, uncertain 2-tuple linguistic weighted Muirhead mean (UL2–tuple-WMM) operator. In addition, we extend UL2–tuple-WMM operator to a new aggregation operator named extended uncertain 2-tuple linguistic weighted Muirhead mean (EUL2–tuple-WMM) operators in order to handle some decision-making problems with ULI2–tuple whose attribute values are expressed in ULI2–tuple and attribute weights are also 2-tuple linguistic information. Whilst, the some properties of these new aggregation operators are obtained and some special cases are discussed. Moreover, we propose a new method to solve the MAGDM problems with ULI2–tuple. Finally, a numerical example is given to show the validity of the proposed method and the advantages of proposed method are also analysed

    A Novel Multiple Attribute Satisfaction Evaluation Approach with Hesitant Intuitionistic Linguistic Fuzzy Information

    Get PDF
    This paper investigates the multiple attribute decision making (MADM) problems in which the attribute values take the form of hesitant intuitionistic linguistic fuzzy element (HILFE). Firstly, motivated by the idea of intuitionistic linguistic variables (ILVs) and hesitant fuzzy elements (HFEs), the concept, operational laws, and comparison laws of HILFE are defined. Then, some aggregation operators are developed for aggregating the hesitant intuitionistic linguistic fuzzy information, such as hesitant intuitionistic linguistic fuzzy weighted aggregation operators, hesitant intuitionistic linguistic fuzzy ordered weighted aggregation operators, and generalized hesitant intuitionistic linguistic fuzzy weighted aggregation operators. Moreover, some desirable properties of these operators and the relationships between them are discussed. Based on the hesitant intuitionistic linguistic fuzzy weighted average (HILFWA) operator and the hesitant intuitionistic linguistic fuzzy weighted geometric (HILFWG) operator, an approach for evaluating satisfaction degree is proposed under hesitant intuitionistic linguistic fuzzy environment. Finally, a practical example of satisfaction evaluation for milk products is given to illustrate the application of the proposed method and to demonstrate its practicality and effectiveness

    Fuzzy Logic in Decision Support: Methods, Applications and Future Trends

    Get PDF
    During the last decades, the art and science of fuzzy logic have witnessed significant developments and have found applications in many active areas, such as pattern recognition, classification, control systems, etc. A lot of research has demonstrated the ability of fuzzy logic in dealing with vague and uncertain linguistic information. For the purpose of representing human perception, fuzzy logic has been employed as an effective tool in intelligent decision making. Due to the emergence of various studies on fuzzy logic-based decision-making methods, it is necessary to make a comprehensive overview of published papers in this field and their applications. This paper covers a wide range of both theoretical and practical applications of fuzzy logic in decision making. It has been grouped into five parts: to explain the role of fuzzy logic in decision making, we first present some basic ideas underlying different types of fuzzy logic and the structure of the fuzzy logic system. Then, we make a review of evaluation methods, prediction methods, decision support algorithms, group decision-making methods based on fuzzy logic. Applications of these methods are further reviewed. Finally, some challenges and future trends are given from different perspectives. This paper illustrates that the combination of fuzzy logic and decision making method has an extensive research prospect. It can help researchers to identify the frontiers of fuzzy logic in the field of decision making

    PENGEMBANGAN MODEL PENGAMBILAN KEPUTUSAN DENGAN UNIFIKASI DATA NUMERIK DAN FUZZY LINGUISTIK UNTUK ASESMEN HASIL BELAJAR

    Get PDF
    Assessment of learning can be viewed as a decision-making model, because it deals with the process of giving a decision on the quality or performance of student achievement in a number of competency standards. Final result of the decision is usually presented in a figure, and is not accompanied by a description of the achievement of each competency. In the assessment process, teacher’s preferences to students’ performance of the competencies are provided through various techniques, both test and non test, generally in a numeric value, and then in the final results are interpreted into letters or linguistic value. In the proposed model, linguistic variables are exploited as a form of teacher’s preferences in non-test techniques. Consequently, the assessment data set will consist of numerical and linguistic information, so it requires a method to unify them to obtain the final value. The 2-tuple linguistic approach is used in this model since it is better than other linguistic approach in solving the problem of unification linguistic and numerical information. In addition, the 2-tuple linguistic representation are appropriate for this model in order to provide the final results that equipped with the description of achievements of each competency, in order to produce a valid, fair and reliable assessment

    MULTI-ATTRIBUTE DECISION MAKING METHOD BASED ON BONFERRONI MEAN OPERATOR AND POSSIBILITY DEGREE OF INTERVAL TYPE-2 TRAPEZOIDAL FUZZY SETS

    Get PDF
    Abstract. This paper proposes a new approach based on Bonferroni mean operator and possibility degree to solve fuzzy multi-attribute decision making (FMADM) problems in which the attribute value takes the form of interval type-2 fuzzy numbers. We introduce the concepts of interval possibility mean value and present a new method for calculating the possibility degree of two interval trapezoidal type-2 fuzzy sets (IT2 TrFSs). Then, we develop two aggregation techniques, which are called the interval type-2 trapezoidal fuzzy Bonferroni mean (IT2TFBM) operator and the interval type-2 trapezoidal fuzzy weighted Bonferroni mean (IT2TFWBM) operator. We study their properties and discuss their special cases. Based on the IT2TFWBM operator and the possibility degree, a new method of multi-attribute decision making with interval type-2 trapezoidal fuzzy information is proposed. Finally, an illustrative example is given to verify the developed approaches and to demonstrate their practicality and effectiveness

    HEDGE ALGEBRAS, THE SEMANTICS OF VAGUE LINGUISTIC INFORMATION AND APPLICATION PROSPECTIVE

    Get PDF
    The report aims to show that hedge algebras model actually the proper qualitative semantics of words of linguistic variables based on the argument that the inherent qualitative semantics of words should be expressed through the order relationships, induced by the word semantics, between the words in their respective variable domains, as required by decision making of human daily lives. This makes the hedge algebra based approach to the word semantics quite different from the existing approaches and become the only approach that can immediately deal with the natural qualitative semantics of words. We explain clearly and systematically distinguished features and properties of this approach to show that these seem to make the approach to be sound and ensure its effectiveness in applications. This approach seems to be promising for development of hedge algebra-based method to solve problems in various application fields. For illustration, we will give a short overview of effective results some of the initial applications of hedge algebras in the fields of knowledge based systems and in fuzzy control

    Intuitionistic fuzzy generalized probabilistic ordered weighted averaging operator and its application to group decision making

    Get PDF
    In this paper, we present the intuitionistic fuzzy generalized probabilistic ordered weighted averaging (IFGPOWA) operator. It is a new aggregation operator that uses generalized means in a unified model between the probability and the OWA operator. The main advantage of this new operator is that it is able to deal with probabilities (objective information) and ordered weighted averages (subjective information) in the same formulation. Moreover, it is also able to deal with uncertain environments that can be assessed with intuitionistic fuzzy numbers. Furthermore, it uses generalized means providing a very general formulation that includes a wide range of situations. We study some of its main properties and particular cases such as the generalized intuitionistic fuzzy ordered weighted averaging (GIFOWA) operator and intuitionistic fuzzy probabilistic ordered weighted averaging (IFPOWA) operator. We end the paper by applying the new operator to a group decision making problem concerning the selection of investments. First published online: 26 Jun 201

    Dynamic adaptation of user profiles in recommender systems

    Get PDF
    In a period of time in which the content available through the Internet increases exponentially and is more easily accessible every day, techniques for aiding the selection and extraction of important and personalised information are of vital importance. Recommender Systems (RS) appear as a tool to help the user in a decision making process by evaluating a set of objects or alternatives and aiding the user at choosing which one/s of them suits better his/her interests or preferences. Those preferences need to be accurate enough to produce adequate recommendations and should be updated if the user changes his/her likes or if they are incorrect or incomplete. In this work an adequate model for managing user preferences in a multi-attribute (numerical and categorical) environment is presented to aid at providing recommendations in those kinds of contexts. The evaluation process of the recommender system designed is supported by a new aggregation operator (Unbalanced LOWA) that enables the combination of the information that defines an alternative into a single value, which then is used to rank the whole set of alternatives. After the recommendation has been made, learning processes have been designed to evaluate the user interaction with the system to find out, in a dynamic and unsupervised way, if the user profile in which the recommendation process relies on needs to be updated with new preferences. The work detailed in this document also includes extensive evaluation and testing of all the elements that take part in the recommendation and learning processes

    A Multiple Attribute Decision Making Method Based on Uncertain Linguistic Heronian Mean

    Get PDF
    The Heronian mean is a useful aggregation operator which can capture the interrelationship of the input arguments. In this paper, we develop some Heronian means based on uncertain linguistic variables, such as the generalized uncertain linguistic Heronian mean (GULHM) and uncertain linguistic geometric Heronian mean (ULGHM), and some of their desirable properties are also investigated. Considering the different importance of the input arguments, we define the generalized uncertain linguistic weighted Heronian mean (GULWHM) and uncertain linguistic weighted geometric Heronian mean (ULWGHM). Then, a method of multiple attribute decision making under uncertain linguistic environment is presented based on the GULWHM or the ULWGHM. In the end, an example is given to demonstrate the effectiveness and feasibility of the proposed method
    • …
    corecore