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

Abstract

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.