## 2 Related Works  
[PERSON] et al. [12] proposed a novel CODAS technique to deal with MCDM issues. For assessing the desirability of alternatives, this methodology uses the Euclidean distance (ED) and the taxicab distance (TD) formulae as the primary and supplementary measures, respectively. The negative ideal point is used to calculate both ED and TD. In the CODAS approach, the alternative having the greatest distance is preferred. To solve facility location issues, [PERSON] et al. [13] employed four fuzzy multi-attribute group decision-making (FMAGDM) strategies that took into consideration both quantitative and qualitative criteria. They examined the techniques with respect to computational complexity and discovered FAHP to be very challenging. [PERSON] et al. [14] proposed a two-step fuzzy decision-making methodology to locate the warehouse in a supply chain. In a traditional supply chain system involving market demand unpredictability, they examined the simultaneous optimization of the problem related to multiple conflicting objectives. [PERSON] et al. [15] developed a new FMADM methodology for facility placement difficulties that includes a simple additive weighting mechanism employing the fuzzy technique. The work was not able to tackle challenges involving many facility sites. The FAHP model was utilized by [PERSON] et al. [16] to handle the issues of advanced MCDM in the process of selecting the supplier. [PERSON] et al. [17] developed a comprehensive technique for searching and evaluating the supplier in the management of the supply chain. Suppliers were evaluated in the first round based on qualitative criteria that included service level, financial health, and loyalty. The weights were determined using the FAHP. Fuzzy logic and triangular fuzzy numbers (TFNs), on the other hand, are commonly used to deal with the complexities of human judgment. To develop a multi-objective linear programming (MOLP) model, the assessment and evaluation of suppliers are carried out by utilizing quantitative criteria that include cost price, defect rate, and delay, while taking into account afirm's requirements and the suppliers' limitations. [PERSON] et al. [18] used a hybrid FAHP along with a green DEA model to construct an MCDM framework to deal with durable supplier selection for the manufacturing of edible oil. Depending on the suggestions of the company's procurement professionals, the study used a hybrid MCDM method that incorporated an FAHP, including a GDEA method for determining criteria weights in the procedure for selecting a supplier. The authors of the paper [19] offered the MCDM approach for evaluating and selecting providers of N-hexane solvent (C6H14) in the production of vegetable oil. Experts specified all aspects that impacted the selection of the supplier of the hexane solvent and the inspection process. The criteria weights were then estimated using the FAHP's multi-criteria comparison analysis. Eventually, the technique for order of preference by similarity to ideal solution (TOPSIS) was employed in choosing the optimum provider of the hexane solvent. [PERSON] and [PERSON] [20] described how to find the optimum maintenance mix across various components of aplant's manufacturing process by applying a fuzzy decision-making methodology. [PERSON] and [PERSON] [21] investigated how the FAHP and the fuzzy TOPSIS technique may be utilized to find the best strategy related to the maintenance of a thermal power plant's power production unit. [PERSON] et al. [22] used a TOPSIS model based on an analytic network process (ANP) to find the optimal mining maintenance approach. To investigate the viable maintenance option, [PERSON] et al. [23] suggested a technique called fuzzy multiple-criteria decision-making (FMCDM) that depended on a complex proportional assessment (CORRAS) and an analytic hierarchy process (AHP). The assessment criteria weights were generated using the FAHP, and the alternatives' rankings were determined using the COPRAS technique.