A linguistic decision model for personnel management solved with a linguistic biobjective genetic algorithm
Francisco Herrera, López González, Cristina Mendaña Cuervo, Miguel Angel Rodríguez-Fernández · Zenodo (CERN European Organization for Nuclear Research) · 2001
Abstract Staff selection for the varying activities performed by enterprises requires a coherent approach, which cannot be simplistic, to the information held. The use of flexible computation and the vague representation of knowledge available by means of linguistic labels allow the problem to be recognised as it is in real life. This paper is an attempt to supply a satisfactory solution to a real staff management problem with linguistic information presenting a linguistic decision model for personnel problem. For reaching a good solution, a novelty genetic algorithm with a linguistic biobjective fitness function is proposed.