## 3 Problem Description
### Results of Model Application  
Following the establishment of the problem's structure, encompassing alternatives and the criteria for assessment, the Fuzzy SWARA method was employed to determine the relative weights of the criteria. The defined methodology involves initially ranking the criteria in descending order of importance and subsequently assessing the significance of each criterion relative to the next. Multiple experts participated in this decision-making process; they were tasked with evaluating the criteria and alternatives using the linguistic ratings provided in Table 1. These expert ratings underwent statistical combination through a probability distribution. Opting for grades with the highest probability as representative values for the observed criteria (alternatives), these ratings were numerically transformed based on the ratios specified in Table 1. Fifteen experts, with varying levels of experience, from the field of logistics participated in the process of evaluating the criteria and alternatives. Table 2 illustrates the surveyed experts' experience, and the experts were divided into four groups based on their experience. An approximate number of experts was taken from each group to ensure an objective assessment of the criteria and alternatives.  
Following the expert evaluations of the criteria, coefficient \(\widetilde{\beta}_{j}\) was computed using Equation (1). Subsequently, the preliminary criterion weight \(\widetilde{\delta}_{j}\) was determined using Equation (2), and the relative weight of the criterion, \(\widetilde{w}_{j}\), was derived through Equation (3). Table 3 illustrates the obtained results. In Table 3, the consolidated ratings assigned by the experts are presented. Based on these ratings, the values of coefficients \(\widetilde{\beta}_{j}\), \(\widetilde{\delta}_{j}\), and \(\widetilde{w}_{j}\) and the crisp values of the criterion weights \(w_{j}\) were calculated. The obtained fuzzy SWARA method values were utilized in further calculations for ranking the alternatives.  
After determining the relative weight of the criteria, the experts evaluated the alternatives. The final alternative evaluations were obtained the same way as the criteria evaluations, and the matrix \(\widetilde{F}\) (4) was formed. In Table 4, the aggregated ratings of alternatives across criteria assigned by experts are presented. The consolidated expert ratings were transformed into fuzzy sets and served as input data in the ranking of the alternatives using the ADAM method.  
The weights of the criteria obtained by applying the Fuzzy SWARA method and the alternative evaluations per criterion represent the input data for the ADAM method. For the application of the ADAM method, the software developed by [PERSON] et al. was used [18]. The output from the ADAM method represents the polyhedron volume of each alternative, calculated using Equation (11). The obtained polyhedron volumes represent the values for the alternatives ranking, the values of which are shown in Table 5.  
The ADAM method provides a visualization of the obtained solution, which makes it possible to see the difference in the ranking of the observed alternatives. The output of the ADAM method are the volumes of the three-dimensional complex polyhedra. For each defined alternative,