An Approach for Resilient-Green Supplier Selection Based on WASPAS, BWM, and TOPSIS under Intuitionistic Fuzzy Sets

Table 1

Comparison of this study with previous studies.

Literature	Dimensions		Approach	Theme
	Resilience	Greenness
Kuo et al. [83]		√	Artificial neural network (ANN) + data envelopment analysis (DEA) + analytic network process (ANP)	The integration results of the three methods are better than two other hybrid methods, ANN–DEA and ANP–DEA
Zouggari and Benyoucef [85]		√	Fuzzy AHP + fuzzy TOPSIS	Solving order allocation problem with fuzzy TOPSIS
Hashemi et al. [87]		√	Grey relational analysis (GRA) + analytic network process (ANP)	ANP improves the uncertainty in GRA
Hosseini and Khaled [8]	√		Classification and regression tree (CART)+ neural network (NN) + analytic hierarchy process (AHP)	Hybrid methods with different categories have better prediction resilience than single-category methods
Parkouhi and Ghadikolaei [10]	√		Analytic network process (ANP) + VIKOR	Application of grey number and fuzzy set in model
Amindoust [56]	√	√	Assurance region DEA method (AR-DEA)	Combining sustainable criteria with resilient criteria in supplier selection
Demir et al. [79]		√	VIKOR-based sorting method (VIKORSORT)	VIKORSORT can be used to sort green suppliers into the predefined ordered classes
Proposed method	√	√	BWM + fuzzy WASPAS + fuzzy TOPSIS	Introducing TOPSIS into ranking stage of WASPAS can improve the accuracy and consistency