## 2 Literature Review
The authors applied the methodology to a personnel selection problem to validate the proposed framework. The literature review revealed several applications that combine MCDM to support decision-making in personnel selection problems. In most cases, the authors applied one method to obtain the weights of the criteria and another to evaluate the alternatives, taking advantage of the characteristics of each model. In this work, we analyzed the models and methods of MCDA most applied in personnel problems (Table 1). The sum of the percentages is more than 100% because, in several articles, the authors applied more than one method. Analyzing the results, we observed that fuzzy logic is the most applied modeling in personnel selection problems with MCDM, present in 45% of the analyzed articles. Given the significant subjectivity and uncertainties related to personnel selection, the preponderance is that diffuse approaches deal better with inaccuracy and uncertainty [15]. \begin{table}
\begin{tabular}{c c} \hline \hline
**Modeling/Method** & **Percentage** \\ \hline Fuzzy Logic & 45.76\% \\ TOPSIS & 28.81\% \\ AHP & 18.64\% \\ ANP & 16.95\% \\ VIKOR & 11.86\% \\ SWARA & 11.86\% \\ MULTIMOORA & 10.17\% \\ DemeI & 8.47\% \\ ARAS & 8.47\% \\ ELECTRE & 6.78\% \\ DELPHI & 3.39\% \\ MOORA & 3.39\% \\ PIPRECIA-G & 1.69\% \\ OCRA-G & 1.69\% \\ Interactive and multiple attribute decision making (TODIM) & 1.69\% \\ BWM & 1.69\% \\ COmbinative Distance-based Assessment (CODAS) & 1.69\% \\ PROMETHEE & 1.69\% \\ EDAS & 1.69\% \\ WasPAS & 1.69\% \\ KEMIRA & 1.69\% \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Distribution of MCDM models and methods. These findings corroborate the impressions of several authors, such as [PERSON] and [PERSON] [34], [PERSON] et al. [35], and [PERSON] et al. [14]. They applied fuzzy logic concepts in conjunction with MCDM methods to deal with data characterized by inconsistency and uncertainty in multicriteria problems. Among the methods of MCDM, the TOPSIS and VIKOR stand out, characteristic of problems of ordering or choice. In most of the articles analyzed, the authors used the methods to obtain a ranking of candidates or to select the best employee of a given company. In addition, the AHP, ANP, and SWARA methods are also among the most applied, mainly because they allow the analysis of qualitative and quantitative data. In most cases, we found that these methods are used to obtain the weights of the criteria and other methods of ordering or selection for evaluating alternatives. In general, in this type of problem, there is a preference for compensatory methods to the detriment of non-compensatory methods. We observed several tactical, operational and strategic applications, presenting many hybrid models, combining the characteristics of different multicriteria methods. In addition, significant subjectivity and uncertainties are present in decision-making for personnel selection. In this context, for a methodology to present transparent and reliable results, it is necessary to analyze quantitative and qualitative data in situations where it is impossible to define a precise numerical scale to specific subjective criteria.