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CROSS-ENTROPY MEASURES OF MULTIVALUED NEUTROSOPHIC SETS AND ITS APPLICATION IN SELECTING MIDDLE-LEVEL MANAGER

机译:多值中性集的交叉熵度量及其在中层管理人员选择中的应用

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摘要

Selecting middle-level managers is a key decision-making issue facing human resource professionals. Multivalued neutrosophic sets (MVNSs), a subset of neutrosophic sets (NSs), is a more flexible and effective method for solving practical middle-level manager selection scenarios than fuzzy sets (FSs). In this paper, in order to address middle-level manager selection decision-making issues, cross-entropy of MVNSs is investigated, and several novel cross-entropy measures between two MVNSs are introduced and their related properties are proven. We then propose two approaches based on the developed cross-entropy measures under the multivalued neutrosophic environment, and within these approaches, an optimal model is devised to determine the weight vector of the criteria with completely unknown information. Finally, the proposed methods are applied to the real selection of middle-level managers, and the ranking results are compared with previously proposed methods to show that the proposed methods are practical and effective.
机译:选择中层管理人员是人力资源专业人员面临的关键决策问题。多值中智集(MVNSs)是中智集(NSs)的子集,它是解决实际中层管理者选择方案的一种比模糊集(FSs)更灵活和有效的方法。为了解决中层管理者选拔决策问题,研究了MVNS的交叉熵,并介绍了两种MVNS之间的几种新颖的交叉熵测度,并证明了它们的相关性质。然后,在多值中智环境下,基于已开发的交叉熵测度,提出了两种方法,在这些方法中,设计了一种最优模型来确定完全未知信息的标准的权重向量。最后,将所提出的方法应用于中层管理人员的真实选择,并将排名结果与先前提出的方法进行比较,以证明所提出的方法是切实可行的。

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