A Novel Self-Regulating and Intelligence Meta-Heuristic-Fuzzy Approach for Integrated and Optimal Human Resource Allocation in Normal and Critical Conditions

This study aims to present a novel Self-regulating and Intelligence Meta-Heuristic-Fuzzy approach (As Methodological Contribution) for integrated optimal Human Resource Allocation (HRA) in normal critical conditions at SMEs Conceptual Contribution). In this research, mathematical model of human resource allocation problem is presented, then Sugeno Fuzzy Inference (SFI) used the tasks rate adjustment layer. The SFI main part developing Gray Wolf Optimization (GWO) algorithm reach available resources under self-regulating attribute approach. has tested compared best researches using data previous by top five proposed methods (Includes: SGA, PRS, SRS, MIP, HM) based on three evaluating quality solutions (GA-FSGS, MP-FSGS, GA-SGS). results showed that increase Ω from 15,000 25,000, HM SGA clearly performed better than other cases larger B100 B200 datasets. Also, it verified method had compare all solving methods, have been best.