Research Article

A Parametric Method for Ranking Intuitionistic Fuzzy Numbers and Its Application to Solve Intuitionistic Fuzzy Network Data Envelopment Analysis Models

Table 1

Summary of the literature review.

Ranking IFNs

Studies to develop a ranking method using the expected value conceptGrzegorzewski [13], Ye [15], and Jianqiang and Zong [17]
Studies to develop a ranking method using the statistical viewpointMitchell [16] and Wan [29]
Studies to develop a ranking method using average indexes of membership and nonmembership functionsNan et al. [21] and Verma and Kumar [22]
Studies to develop a ranking method using the distance indexWang and Zhang [18], Aggarwal and Gupta [34], and Li and Chen [31]
Studies to develop a ranking method using score and accuracy indicesLakshmana 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 conceptsLi [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 conceptDas and Guha [30] and Prakash et al. [35]
Studies to develop a ranking method using an integral value of membership and nonmembership functionsNehi [19] and Darehmiraki [38]

IFDEA models
A superefficient cross-DEA model based on the Bayesian network in the interval-intuitionistic fuzzy environmentXu et al. [40]
An intuitionistic fuzzy BCC modelRazavi Hajiagha et al. [41]
Optimistic and pessimistic IFDEA models with triangular intuitionistic fuzzy dataPuri and Yadav [42]
An intuitionistic fuzzy DEA/AR model with triangular intuitionistic fuzzy dataSingh [43]
Intuitionistic fuzzy SBM and superefficiency intuitionistic fuzzy SBM models with triangular intuitionistic fuzzy dataArya and Yadav [44]
An intuitionistic fuzzy CCR model with triangular intuitionistic fuzzy dataArya and Yadav [45]
Intuitionistic fuzzy BCC and intuitionistic fuzzy superefficient BCC models with triangular intuitionistic fuzzy dataArya and Yadav [46]

IFNDEA models
Study to develop a parallel intuitionistic fuzzy network DEA modelAmeri et al. [47]