Open AccessPersonnel selection based on fuzzy methods
Author(s) -
Lourdes Cános Darós,
Trinidad Casasús,
Enric Crespo,
Tomás Lara,
Juan C. Pérez
Publication year - 2011
Publication title -
revista de matemáticas
Language(s) - English
Resource type - Journals
eISSN - 2215-3373
pISSN - 1409-2433
DOI - 10.15517/rmta.v18i1.2122
Subject(s) - fuzzy logic , computer science , competence (human resources) , selection (genetic algorithm) , valuation (finance) , matching (statistics) , software , data mining , artificial intelligence , machine learning , mathematics , business , management , statistics , economics , finance , programming language
The decisions of managers regarding the selection of staff strongly determine the success of the company. A correct choice of employees is a source of competitive advantage. We propose a fuzzy method for staff selection, based on competence management and the comparison with the valuation that the company considers the best in each competence (ideal candidate). Our method is based on the Hamming distance and a Matching Level Index. The algorithms, implemented in the software StaffDesigner, allow us to rank the candidates, even when the competences of the ideal candidate have been evaluated only in part. Our approach is applied in a numerical example.