|
Ranking IFNs |
|
Studies to develop a ranking method using the expected value concept | Grzegorzewski [13], Ye [15], and Jianqiang and Zong [17] |
Studies to develop a ranking method using the statistical viewpoint | Mitchell [16] and Wan [29] |
Studies to develop a ranking method using average indexes of membership and nonmembership functions | Nan et al. [21] and Verma and Kumar [22] |
Studies to develop a ranking method using the distance index | Wang and Zhang [18], Aggarwal and Gupta [34], and Li and Chen [31] |
Studies to develop a ranking method using score and accuracy indices | Lakshmana Gomathi Nayagam et al. [32], Nayagam et al. [33], Singh and Yadav [36], and Canedo and Morales [37] |
Studies to develop a ranking method using value and ambiguity concepts | Li [26], Li et al. [27], Chutia and Chutia [24], Nayagam et al. [28], and Chutia and Saikia [25] |
Studies to develop a ranking method using a centroid concept | Das and Guha [30] and Prakash et al. [35] |
Studies to develop a ranking method using an integral value of membership and nonmembership functions | Nehi [19] and Darehmiraki [38] |
|
IFDEA models |
A superefficient cross-DEA model based on the Bayesian network in the interval-intuitionistic fuzzy environment | Xu et al. [40] |
An intuitionistic fuzzy BCC model | Razavi Hajiagha et al. [41] |
Optimistic and pessimistic IFDEA models with triangular intuitionistic fuzzy data | Puri and Yadav [42] |
An intuitionistic fuzzy DEA/AR model with triangular intuitionistic fuzzy data | Singh [43] |
Intuitionistic fuzzy SBM and superefficiency intuitionistic fuzzy SBM models with triangular intuitionistic fuzzy data | Arya and Yadav [44] |
An intuitionistic fuzzy CCR model with triangular intuitionistic fuzzy data | Arya and Yadav [45] |
Intuitionistic fuzzy BCC and intuitionistic fuzzy superefficient BCC models with triangular intuitionistic fuzzy data | Arya and Yadav [46] |
|
IFNDEA models |
Study to develop a parallel intuitionistic fuzzy network DEA model | Ameri et al. [47] |
|