1,782 research outputs found

    New group decision making method in intuitionistic fuzzy setting based on TOPSIS

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    In multiple attribute group decision making, the weights of decision makers are very crucial to ranking results and have gained more and more attentions. A new approach to determining experts’ weights is proposed based on the TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) method in intuitionistic fuzzy setting. The weights determined by our method have two advantages: the evaluation value has a large weight if it is close to the positive ideal evaluation value and far from negative ideal evaluation values at the same time, otherwise it is assigned a small weight; experts have different weights for different attributes, which are more appropriate for real decision making problems since each expert has his/her own knowledge and expertise. The multiple attribute intuitionistic fuzzy group decision making algorithm has been proposed which is suitable for different situations about the attribute weight information, including the attribute weights are known exactly, partly known and unknown completely. A supplier selection problem and the evaluation of murals in a metro line are finally used to illustrate the feasibility, efficiency and practical advantages of the developed approaches

    Intertemporal Choice of Fuzzy Soft Sets

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    This paper first merges two noteworthy aspects of choice. On the one hand, soft sets and fuzzy soft sets are popular models that have been largely applied to decision making problems, such as real estate valuation, medical diagnosis (glaucoma, prostate cancer, etc.), data mining, or international trade. They provide crisp or fuzzy parameterized descriptions of the universe of alternatives. On the other hand, in many decisions, costs and benefits occur at different points in time. This brings about intertemporal choices, which may involve an indefinitely large number of periods. However, the literature does not provide a model, let alone a solution, to the intertemporal problem when the alternatives are described by (fuzzy) parameterizations. In this paper, we propose a novel soft set inspired model that applies to the intertemporal framework, hence it fills an important gap in the development of fuzzy soft set theory. An algorithm allows the selection of the optimal option in intertemporal choice problems with an infinite time horizon. We illustrate its application with a numerical example involving alternative portfolios of projects that a public administration may undertake. This allows us to establish a pioneering intertemporal model of choice in the framework of extended fuzzy set theorie

    A new distance measure and corresponding TOPSIS method for interval-valued intuitionistic fuzzy sets in multi-attribute decision-making

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    Strengthening the evaluation of teaching satisfaction plays a crucial role in guiding teachers to improve their teaching quality and competence, as well as in aiding educational institutions in the formulation of effective teaching reforms and plans. The evaluation process for teaching satisfaction is usually regarded as a typical multi-attribute decision-making (MADM) process, which inherently possesses uncertainty and fuzziness due to the subjective nature of human cognition. In order to improve the subtle discrimination of evaluation information data and enhance the accuracy of the evaluation results, we have developed an integrated MADM method by combining a new distance measure and an improved TOPSIS method for interval-valued intuitionistic fuzzy sets (IvIFSs). First, a novel distance measure for IvIFSs based on triangular divergence is proposed to capture the differences between two IvIFSs, and some properties of this distance measure are investigated. Then, the superiority of this new distance measure is compared with some existing distance measures. Afterward, an improved TOPSIS method is also established based on the proposed triangular distance under the interval-valued intuitionistic fuzzy setting. Besides, to illustrate the practicality of the new method, a numerical example is presentedto evaluate mathematics teaching satisfaction. Moreover, a comparative analysis that includes existing TOPSIS methods, is presented to demonstrate the superiority of the given method. The comparison outcomes show that the proposed technique can effectively discern uncertainties or subtle differences in IvIFSs, resulting in more accurate and comprehensive evaluation results for teaching satisfaction. Overall, the findings of this study emphasize the importance of incorporating the new distance measure in MADM. The proposed approach serves as a valuable tool for decision-makers to compare and evaluate alternatives effectively

    Sustainability performance assessment with intuitionistic fuzzy composite metrics and its application to the motor industry

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    The performance assessment of companies in terms of sustainability requires to find a balance between multiple and possibly conflicting criteria. We here rely on composite metrics to rank a set of companies within an industry considering environmental, social and corporate governance criteria. To this end, we connect intuitionistic fuzzy sets and composite programming to propose novel composite metrics. These metrics allow to integrate important environmental, social and governance principles with the gradual membership functions of fuzzy set theory. The main result of this paper is a sustainability assessment method to rank companies within a given industry. In addition to consider multiple objectives, this method integrates two important social principles such as maximum utility and fairness. A real-world example is provided to describe the application of our sustainability assessment method within the motor industry. A further contribution of this paper is a multicriteria generalization of the concept of magnitude of a fuzzy number

    An approach to multiple attribute decision making based on the induced Choquet integral with fuzzy number intuitionistic fuzzy information

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    In this paper, we investigate the multiple attribute decision making problems with fuzzy number intuitionistic fuzzy information. Firstly, some operational laws of fuzzy number intuitionistic fuzzy values, score function and accuracy function of fuzzy number intuitionistic fuzzy values are introduced. Then, we have developed two fuzzy number intuitionistic fuzzy Choquet integral aggregation operators: induced fuzzy number intuitionistic fuzzy choquet ordered averaging (IFNIFCOA) operator and induced fuzzy number intuitionistic fuzzy choquet ordered geometric (IFNIFCOG) operator. The prominent characteristic of the operators is that they can not only consider the importance of the elements or their ordered positions, but also reflect the correlation among the elements or their ordered positions. We have studied some desirable properties of the IFNIFCOA and IFNIFCOG operators, such as commutativity, idempotency and monotonicity, and applied the IFNIFCOA and IFNIFCOGM operators to multiple attribute decision making with fuzzy number intuitionistic fuzzy information. Finally an illustrative example has been given to show the developed method
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