# A New Integrated Multi-Criteria Decision-Making Model for Resilient Supplier Selection
## 2 Literature  
The trend of research in supplier selection indicates that the SC focus has been shifted from conventional, green and sustainability elements towards resilience to deal with uncertainties and incomplete information caused by unexpected risks and disruptions. In previous studies [3; 8], researchers have proposed different MCDM techniques for resilient supplier selection such as VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), Additive Ratio Assessment (ARAS), Weighted Aggregated Sum Product Assessment (WASPAS), Data Envelopment Analysis (DEA), Analytical Network Process (ANP),Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Multi-Choice Goal Programming (MCGP), Fuzzy Inference System (FIS) and Analytical Hierarchy Process (AHP). Some of the latest studies are presented in this section. [PERSON] et al. [3] proposed a hybrid MCDM approach towards resilient sourcing. They developed an efficient resilient supplier selection approach based on a new holistic framework that enables the identification of key resilience pillars (RPs) and traditional business criteria (TBC). The outcome was the measurement of the relative importance of TBC and RP by applying the DEMATEL method. This was followed by the integration of Multi-Attributive Border Approximation Area Comparison (MABAC) and Operational Competitiveness Rating Analysis (OCRA) with TOPSIS and VIKOR methods in verifying the suppliers' ranking. [PERSON] et al. [9] presented a soft computing approach to mitigate uncertainties in resilient supplier selection. Considering both the tangible and intangible criteria, they presented a new integrated fuzzy AHP and fuzzy ARAS with fuzzy entropy using the linguistic values to solve the supplier selection problem with uncertain data. Fuzzy entropy was used to obtain the entropy weights of the criteria while fuzzy AHP-ARAS was applied to rank the suppliers. A hybrid model was proposed by [PERSON] et al. [10] for green-resilient supplier selection which integrated BWM, WASPAS, and TOPSIS to select green-resilient suppliers. Firstly, the criteria weights were calculated by BWM and the intuitionistic fuzzy numbers were applied to rank the suppliers. Then, WASPAS-TOPSIS was applied to select the optimal resilient-green supplier. [PERSON] et al. [11] developed a Decision Support System (DSS) to incorporate imprecise heterogeneous data to rank the resilient suppliers in a logistic 4.0 environment. They induced a triangular fuzzy number from large-scale temporal data by applying the probability-possibility consistency principle. The qualitative attributes were mapped by the fuzzy linguistic variables while the suppliers were ranked by the fuzzy-based TOPSIS method. These ranking scores act as the inputs of the MCGP model to determine the optimal order allocation for the suppliers. In a latter study conducted by [PERSON] [12], an integration between a grey theory with DEMATEL-VIKOR was proposed for the resilient supplier selection. After identifying the presilience criteria, the DEMATEL algorithm was used to determine the importance levels of criteria based on the experts' opinions. The presilience performances of suppliers were then assessed by using the VIKOR algorithm. Next, the suppliers' performances were revealed and the insights for the presilience suppliers were discussed. In another study, [PERSON] et al. [13] employed a two-stage methodology for the supplier selection process. Their aim was to determine the resilient capability factors at different stages of SC disruptions in Pakistan's textile industry. In the first stage, the resilient capability factors were identified through the experts' consultations. In the second stage, the factors needed for the textile industry were ranked by applying AHP. [PERSON] et al. [14] considered two dimensions which were resilience enhancer and resilience reducer in selecting suppliers.