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A novel extension to VIKOR method under intuitionistic fuzzy context for solving personnel selection problem

机译:关于求解人员选择问题的直观模糊背景下的Vikor方法的一种新颖延伸

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摘要

Personnel selection is a challenging problem for any organization. The success of a project is determined by the human resources that handle the project. To make better personnel selections, researchers have adopted multi-criteria decision-making (MCDM) approaches. Among these, fuzzy-based MCDM methods are most frequently used, as they handle vagueness and imprecision better. Intuitionistic fuzzy set (IFS) is a popular MCDM context which provides degree of membership and non-membership for preference elicitation. In this work, we propose a novel decision-making framework that consists of two stages. In the first stage, a new extension to the popular VIKOR method is presented under IFS context. The positive and negative ideal solutions are determined, and VIKOR parameters are calculated using transformation procedure. The proposed method combines the strength of both interval-valued fuzzy set and IFS that is more effective in handling vagueness with a simple formulation setup. In the second stage, a personnel selection problem is used to validate the proposed framework. Finally, the superiority and weakness of the proposed framework are discussed by comparison with other methods.
机译:人员选择对任何组织都是一个具有挑战性的问题。项目的成功由处理项目的人力资源决定。为了更好的人才选择,研究人员采用了多标准决策(MCDM)方法。其中,基于模糊的MCDM方法最常使用,因为它们更好地处理模糊和不精确。直觉模糊集(IFS)是一个流行的MCDM上下文,提供了偏好诱因的成员资格和非成员资格。在这项工作中,我们提出了一种由两个阶段组成的新型决策框架。在第一阶段,在IFS上下文中介绍了流行Vikor方法的新扩展。确定正负理想解决方案,使用转换过程计算Vikor参数。所提出的方法结合了间隔值模糊集的强度,以及用简单的配方设置处理模糊性更有效的IF。在第二阶段,人员选择问题用于验证所提出的框架。最后,通过与其他方法进行比较讨论了所提出的框架的优越性和弱点。

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