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The incorporation of new personnel or the reallocation of existing tasks is an important decision, sinceits correctness will determine the survival of the company. In this context, having a model of personnelselection, that considers the associated ambiguous information and degrees of uncertainty, becomes relevantwhen assessing the qualitative value of the applicants, able to deliver accurate and precise results thusensuring the good performance of the position and reducing the associated risk with the incorporationof new people. In this work, a model of personnel selection, in conditions of uncertainty using fuzzylogic and having as input the data descriptions of positions of a retail industry, with triangular fuzzyvariables and overlap was developed. This was compared with a classical model of multiple regressions.The results showed in this case, that the use of the model of multiple regressions is more efficient thanthe opted model of fuzzy logic

Lógica difusa vs. modelo de regresión múltiple para la selección de personal