Premium
Personnel selection based on intuitionistic fuzzy sets
Author(s) -
Boran Fatih Emre,
Genç Serkan,
Akay Diyar
Publication year - 2011
Publication title -
human factors and ergonomics in manufacturing and service industries
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.408
H-Index - 39
eISSN - 1520-6564
pISSN - 1090-8471
DOI - 10.1002/hfm.20252
Subject(s) - vagueness , topsis , selection (genetic algorithm) , ideal solution , computer science , fuzzy set , fuzzy logic , similarity (geometry) , set (abstract data type) , function (biology) , operations research , data mining , artificial intelligence , mathematics , physics , evolutionary biology , biology , image (mathematics) , thermodynamics , programming language
One of the most important activities carried out by human resource management is personnel selection, concerned with identifying an individual from a pool of candidates suitable for a vacant position. Traditionally, personnel selection is a group decision‐making problem under multiple criteria containing subjectivity, imprecision, and vagueness, which are best represented with fuzzy data. In this article, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method extended to intuitionistic fuzzy environments is proposed to select appropriate personnel among candidates. An intuitionistic fuzzy set (IFS), which is characterized by membership function, nonmembership function, and hesitation margin, is a more suitable way to deal with vagueness when compared to a fuzzy set. To demonstrate the applicability and effectiveness of the intuitionistic fuzzy TOPSIS method, a numerical example of personnel selection in a manufacturing company for a sales manager position is given. © 2011 Wiley Periodicals, Inc.