Table 20 Core features and limitations for different techniques.
Method | Core features | Limitations |
|---|---|---|
2TLNNWA/2TLNNWG | Weighted averaging (WA) or geometric mean (WG) based aggregation operators with simple computation | Cannot handle inter-attribute relationships and ignores decision-makers’ psychological behavior |
2TLNNWMM/WDMM | Uses Maclaurin symmetric mean (WMM/WDMM) to capture inter-attribute interactions | Computationally complex and lacks integration of behavioral decision factors like risk preference |
2TLNN-MABAC | Border approximation area comparison (MABAC) based, suitable for boundary-sensitive decision problems | Lacks psychological behavior analysis in fuzzy linguistic environments |
2TLNN-CODAS | Combinative distance-based assessment (CODAS), suitable for high-precision ranking | Relies on distance measures |
2TLNN-GRA | Grey relational analysis (GRA), effective for small samples or incomplete information | Does not consider decision-makers’ risk attitudes, which may affect result rationality |
2TLNN-TODIM | Based on prospect theory, can simulate decision-makers’ risk aversion behavior | Only uses traditional TODIM without relational analysis, potentially affecting stability |
Proposed method (2TLNN-Com-ExpTODIM-GRA) | Combines TODIM’s behavioral decision-making + GRA’s relational analysis + Exponential function for enhanced sensitivity | Slightly higher computational complexity but significantly improved comprehensive performance |
