The goal of this research was to find a selection of green suppliers (GSS) that will, in the best way, help agricultural producers to apply green agricultural production using uncertainty in decision making. In order to avoid the possibility of uncertainty in the expert decision making, Z-numbers were used together with the fuzzy LMAW (Logarithm Methodology of Additive Weights) method and fuzzy CRADIS (Compromise Ranking of Alternatives from Distance to Ideal Solution) method. By applying Z-numbers and the fuzzy LMAW method, the weighting coefficients of the criteria were determined, where the experts, in addition to the criteria ratings, also defined the degrees of certainty in the criteria ratings they gave. The obtained results indicated that the criteria related to price and qualities are the most important during the selection process. To select the best alternative, the CRADIS method modified with Z-numbers and fuzzy numbers was applied. The results obtained by applying this method showed that suppliers A2 and A3 have the best characteristics and are the first choice for the procurement of raw and production materials. As part of the paper, the validation of the results and the sensitivity analysis of the model were carried out by conducting the procedure of comparing the obtained results with the results obtained by other MCDM methods and changing the weighting coefficients of the criteria. These analyses indicated that the model presented provides stable results. The conducted research showed how Z-numbers can be used to reduce uncertainty in decision making and how Z-numbers can be used with other fuzzy methods to perform GSS.

Understanding the level of economic freedom is an important indicator for investors and policymakers. The index of economic freedom, which the Heritage Foundation releases annually, is the most significant of the methods used to measure this indicator in practice, as this index evaluates the degree of market openness over the degree of fiscal and regulatory restraint. The research presented in this paper was conducted in order to establish the level of economic freedom in the Balkan countries. For this purpose, a multi-criteria ranking of Balkan countries based on economic freedom criteria was used. The weight of the criteria was determined using the Entropy method, and the countries were ranked using the CRADIS (Compromise Ranking of Alternatives from Distance to ideal Solution) method. These methods employed a double normalisation approach, and according to the results of this application, Bulgaria has the best indicators of economic freedom, while Montenegro has the worst, with sensitivity analysis and validation of the results confirming these findings. The approach of using double normalisation contributes to decision-making stability since the results of different methods are uniform when compared to the use of the classical approach in the case of multi-criteria analysis methods.

A decision-making process requires a prior definition and fulfilment of certain factors, especially when it refers to complex fields such as supply chain management. One of the most important items in the initial stage of a supply chain, which strongly influences its further flow, is making a decision on the most suitable supplier. In this paper, a model for evaluation and supplier selection has been proposed, which has been considered in more than ten different production areas. The model consists of twenty quantitative and qualitative criteria, which are reduced to a total of nine by the application of the fuzzy AHP and the assessment of managers in production companies. The verification of the model has been presented throughout a selection of suppliers in a company for the production of plastic bags and foils, where the Fuzzy Analytic Hierarchy Process (Fuzzy AHP) method has been used to determine the significance of the criteria, and the Fuzzy Evaluation based on Distance from Average Solution (Fuzzy EDAS) to evaluate and select suppliers. The obtained results have been considered throughout a sensitivity analysis in which a total of 15 different scenarios have been formed and where the stability of the model has been determined, since the supplier one is the best solution in all the cases.