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Q-rung orthopair fuzzy multiple attribute group decision-making method based on normalized bidirectional projection model and generalized knowledge-based entropy measure

机译:基于归一化双向投影模型的Q-rung orthopair模糊多属性组决策方法和基于广义知识熵测量的基于归一化双向投影模型

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摘要

The q-rung orthopair fuzzy sets (q-ROFSs) can serve as a generalization of intuitionistic fuzzy sets (IFSs) and Pythagorean fuzzy sets (PFSs). q-ROFSs provide more freedom for decision makers in describing their opinions than other ordinary orthopair fuzzy sets. In this paper, a novel multiple attribute group decision making(MAGDM) method is constructed under q-rung orthopair fuzzy (q-ROF) environment. First, considering the projection measure provides the distance and the angle between two alternatives simultaneously, this work investigates a new normalized bidirectional projection model (NBPM) of q-ROFSs. By combining the proposed NBPM with Jaynes maximum entropy method, a nonlinear programming model is constructed to calculate the objective attribute weight information. Second, we present a new entropy measure based on the proposed generalized p-norm knowledge-based measure which takes into account both the membership and non-membership functions and the inherent fuzziness of q-ROFSs. Then the weights of decision makers are given by the proposed entropy measure. Furthermore, an integrated MAGDM framework is presented by using the weight determination methods of decision makers and attributes under q-ROF environment. Finally, an illustrative example is given to illustrate the operation process of the proposed decision-making method, sensitivity analysis and comparison analysis are also performed to show the effectiveness and superiority of the proposed method.
机译:Q-RONG Orthopair模糊组(Q-ROFS)可以作为直觉模糊集(IFSS)和Pythagorean模糊集(PFSS)的概括。 Q-ROFSS为决策者提供更多的自由来描述他们的意见,而不是其他普通的北面骨灰模糊套。在本文中,在Q-rsg Orthopair模糊(Q-ROF)环境下构建了一种新的多个属性组决策(MAGDM)方法。首先,考虑投影测量的同时提供两个替代方案之间的距离和角度,该工作研究了Q-rofs的新标准化双向投影模型(NBPM)。通过将所提出的NBPM与Jaynes最大熵方法组合,构造非线性编程模型以计算目标属性权重信息。其次,我们提出了一种新的熵措施,基于所提出的广义P-Nork知识措施,该措施考虑了成员资格和非隶属函数以及Q-ROF的固有模糊性。然后由建议的熵措施给出决策者的重量。此外,通过使用Q-Rof环境下的决策者和属性的权重确定方法来提出集成的MAGDM框架。最后,给出了说明性示例来说明所提出的决策方法的操作过程,还进行了敏感性分析和比较分析,以显示所提出的方法的有效性和优越性。

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