An Optimized Framework fHepN - Approach on Staff Selection in Human Resource Management

In this Study we represent an optimized model to address uncertainty and
vagueness inherent in staff selection processes within Human Resource Management. We
make use of the Fuzzy Heptagonal Number fHepN approach that allows linguistic
variables through six-parameter fuzzy numbers, enhancing the precision of candidate
evaluations across multiple criteria. The proposed Robust’s ranking methodology
incorporates expert judgments, fuzzy aggregation, and defuzzification techniques within
a multi-criteria decision-making (MCDM) framework to generate a comprehensive
candidate ranking. Validation through a case study confirms to deliver consistent and
transparent selection outcomes, in HR decision-making. . The results highlight the
approach’s effectiveness in supporting HR managers to make better recruitment decisions
under uncertainty. This research contributes a novel decision-support tool that advances
the application of fuzzy logic techniques in HRM