101 research outputs found

    Q-rung orthopair normal fuzzy aggregation operators and their application in multi-attribute decision-making

    Get PDF
    © 2019 by the authors. Q-rung orthopair fuzzy set (q-ROFS) is a powerful tool to describe uncertain information in the process of subjective decision-making, but not express vast objective phenomenons that obey normal distribution. For this situation, by combining the q-ROFS with the normal fuzzy number, we proposed a new concept of q-rung orthopair normal fuzzy (q-RONF) set. Firstly, we defined the conception, the operational laws, score function, and accuracy function of q-RONF set. Secondly, we presented some new aggregation operators to aggregate the q-RONF information, including the q-RONF weighted operators, the q-RONF ordered weighted operators, the q-RONF hybrid operator, and the generalized form of these operators. Furthermore, we discussed some desirable properties of the above operators, such as monotonicity, commutativity, and idempotency. Meanwhile, we applied the proposed operators to the multi-attribute decision-making (MADM) problem and established a novel MADM method. Finally, the proposed MADM method was applied in a numerical example on enterprise partner selection, the numerical result showed the proposed method can effectively handle the objective phenomena with obeying normal distribution and complicated fuzzy information, and has high practicality. The results of comparative and sensitive analysis indicated that our proposed method based on q-RONF aggregation operators over existing methods have stronger information aggregation ability, and are more suitable and flexible for MADM problems

    MADM Using m-Generalized q-Neutrosophic Sets

    Get PDF

    Improved Knowledge Measures for q-Rung Orthopair Fuzzy Sets

    Get PDF
    The q-rung orthopair fuzzy set (qROFS) defined by Yager is a generalization of Atanassov intuitionistic fuzzy set (IFS) and Pythagorean fuzzy sets (PyFSs). In this paper, we define the knowledge measure for qROFS by using the cosine inverse function. The information precision and information content are two facets of knowledge measure. Both facets of knowledge measure are considered. The properties of knowledge measure and their graphical explanations are discussed. An application of the knowledge measure in multi-attribute group decision-making (MAGDM) problem under the confidence level approach is given. A numerical example of the selection of renewable energy sources is discussed

    Group Decision Algorithm for Aged Healthcare Product Purchase Under q-Rung Picture Normal Fuzzy Environment Using Heronian Mean Operator

    Get PDF
    With the intensification of the aging, the health issue of the elderly is arousing public concern increasingly. Various healthcare products for the elderly are emerging from the market, thus how to select suitable aged healthcare product is critical to the well-being of the elderly. In the literature, nonetheless, a comprehensive and standardized evaluation framework to support healthcare product purchase decision for the aged is currently lacking. This paper proposes a novel group decision-making method to aid the decision-making of aged healthcare product purchase based on q-rung picture normal fuzzy Heronian mean (q-RPtNoFHM) operators. In it, firstly, a new fuzzy variable called the q-rung picture normal fuzzy set (q-RPtNoFS) is defined to reasonably describe different responses to healthcare product evaluation, for which, some definitions including operational laws, a score function, and an accuracy function of q-RPtNoFSs are introduced. Then, two q-RPtNoFHM operators are presented to aggregate group decision information. In addition, some properties of q-RPtNoFHM operators, such as monotonicity, commutativity, and idempotency, are discussed. Finally, an example on antihypertensive drugs purchase is gave to illustrate the practicality of the proposed method, and conduct sensitivity analysis to analyze the effectiveness and flexibility of proposed methods

    A Decision Support System for Assessing and Prioritizing Sustainable Urban Transportation in Metaverse

    Get PDF
    Blockchain technology and metaverse advancements allow people to create virtual personalities and spend time online. Integrating public transportation into the metaverse could improve services and collect user data. This study introduces a hybrid decision-making framework for prioritizing sustainable public transportation in Metaverse under q-rung orthopair fuzzy set (q-ROFS) context. In this regard, firstly q-rung orthopair fuzzy (q-ROF) generalized Dombi weighted aggregation operators (AOs) and their characteristics are developed to aggregate the q-ROF information. Second, a q-ROF information-based method using the removal effects of criteria (MEREC) and stepwise weight assessment ratio analysis (SWARA) models are proposed to find the objective and subjective weights of criteria, respectively. Then, a combined weighting model is taken to determine the final weights of the criteria. Third, the weighted sum product (WISP) method is extended to q-ROFS context by considering the double normalization procedures, the proposed operators and integrated weighting model. This method has taken the advantages of two normalization processes and four utility measures that approve the effect of benefit and cost criteria by using weighted sum and weighted product models. Next, to demonstrate the practicality and effectiveness of the presented method, a case study of sustainable public transportation in metaverse is presented in the context of q-ROFSs. The findings of this study confirms that the proposed model can recommend more feasible performance while facing numerous influencing factors and input uncertainties, and thus, provides a wider range of application
    • …
    corecore