Multimoora–FG: a multi–objective decision making method for linguistic reasoning with an application to personnel selection

2012-06-29
Multimoora–FG: a multi–objective decision making method for linguistic reasoning with an application to personnel selection

Abstract. This paper aims to extend fuzzy MULTIMOORA with linguistic reasoning and group decision-making (MULTIMOORA-FG). The new method consists of the three parts, namely the fuzzy Ratio System, the fuzzy Utopian Reference Point, and the fuzzy Full Multiplicative Form offering a robust comparison of alternatives against multiple objectives. In addition, MULTIMOORA-FG is designed to deal with triangular fuzzy numbers which, in turn, can resemble linguistic variables. MULTIMOORA-FG is a proper instrument for linguistic reasoning under fuzzy environment. In our study an application of personnel selection illustrates the group decision-making procedure according to MULTIMOORA-FG. Given the uncertainties peculiar of personnel selection, the application of multi-objective decision making (MODM) is required in this area. Fuzzy MULTIMOORA enables to aggregate subjective assessments of the decision-makers and thus offer an opportunity to perform a more robust personnel selection. The committee decided to consider eight qualitative characteristics expressed in linguistic variables. A numerical example exhibited possibilities for improvement of human resources management or any other business decision-making by applying MULTIMOORA-FG.

Keywords: personnel selection; personnel management; employment decisions; human resources management; multi-objective optimization; MULTIMOORA; MULTIMOORA-FG; fuzzy number; linguistic reasoning.

Baležentis, A; Baležentis, T.; Brauers, W. K. M. Multimoora-FG: a multi-objective decision making method for linguistic reasoning with an application to personnel selection // Informatica, ISSN 0868-4952, 23(2), 2012, p. 173-190 (IAOR (International Abstracts in Operations Research), INSPEC, MathSciNet, Science Citation Index Expanded (Web of Science), SCOPUS, VINITI, Zentralblatt MATH).

Impact factor / Agregate Impact factor 1.786 / 1.25.