## 6 Results and Discussion
The averages of the criteria weights \(\overline{\omega}_{i}\) and priorities show a similar trend of their significance as determined by ARTIW-L, ARTIW-N, and DPW methods. However, the significance of the most important criterion D was obtained even higher (\(\omega_{D}=0.2038\)), the significance of the least important criterion H was lower (\(\omega_{H}=0.0376\)). The inverse linear (ARTIW-L method) and non-linear (ARTIW-N, DPW, and AHP methods) correlation was obtained between the average \(\overline{R}_{i}\) of the ranks of ten criteria determined by different MCDM methods and the calculated weights \(\omega_{i}\) of these criteria (Figure 3). The dependence of criteria weights \(\omega_{i}\) on \(\overline{R}_{i}\) is shown by regression equations. The coefficients of determination \(R_{2}\) of these equations are equal to 1 (functional association) or very close to it (strong correlation association). Among these variables (\(\overline{R}_{i}\) and \(\omega_{i}\)), the  
\begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline \multicolumn{1}{c}{**Expert**} & \multicolumn{1}{c}{**Criterion, (i = 1, 2, \(\ldots\), m)**} & & & & & & & \\ \(\mathbf{j=1,2,\ldots,n}\) & \(\mathbf{A}\) & \(\mathbf{B}\) & \(\mathbf{C}\) & \(\mathbf{D}\) & \(\mathbf{E}\) & \(\mathbf{F}\) & \(\mathbf{G}\) & \(\mathbf{H}\) & \(\mathbf{I}\)  
strongest correlation was obtained by the ARTIW-L method (\(R_{2}\) = 1), and the weakest by the DPW method (\(R_{2}\) = 0.9571). The priorities of the criteria according to their calculated normalized subjective weights \(\omega_{i}\) are as follows: \(D\succ J\succ G\succ F\succ E\succ I\succ B\succ A\succ C\succ H\) (Figure 4). The \(\omega_{i}\) values of the four most important criteria (D, J, G, F) are greater than 0.1, i.e., for the average weight of the criteria. The \(\omega_{i}\) of the other six criteria (E, I, B, A, C, H) are lower than 0.1. Arithmetic averages of the percentage weights of the 10 criteria determined by these methods show that the most significant factors (criteria) increasing the RR in the country for experts are the relevance of regulatory documents (18.1%), the asphalt pavement recycling strategy (15.4%), and the homogeneity and sorting of RAP (14.0%). Of lesser importance are RAP ownership and economic utility (10.5%), personnel qualification and experience (9.6%), quality of renewable materials (8.5%), and number and performance of recycling equipment (7.5%). The experts believe that asphalt pavement wear and tear (6.0%), number and productivity of road milling machines (5.3%), and number and capacity of RAP stocks (5.1%) are the least significant. The highest weights of almost half of the most important criteria were obtained by the AHP method. The weights of the other half of the less important criteria were the lowest when calculated also by the AHP method. This shows that the AHP method is the most \"sensitive\" in determining the significance of the criteria, since the difference between the largest and smallest weights determined by the \(k\)-th method (\(k\) = 1, 2,..., \(r\)) \(\Delta\omega_{k}=\omega_{\rm{Imax}}-\omega_{\rm{Imin}}\) is the largest (Figure 5a), i.e., it increases the importance of the most important criteria and decreases the importance of the least important criteria. \begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline \hline \multicolumn{1}{c}{**Expert**} & \multicolumn{1}{c}{**Criterion, (i = 1, 2,..., m)**} & & & & & & & \multicolumn{1}{c}{\(C.R.\)} \\ \multicolumn{1}{c}{**j = 1, 2,..., n**} & **A** & **B** & **C** & **D** & **E** & **F** & **G** & **H** & **I** & **J** & \\ \hline E1 & 0.0195 & 0.0791 & 0.0289 & 0.1900 & 0.0413 & 0.1  
\[\overline{R}=\frac{1}{2}n(m+1)=\frac{1}{2}14(10+1)=77,\]2 The importance (weights) of the factors (criteria) increasing the relative amount of asphalt pavement recycling \(K_{Rac}\) in the country were determined using four different methods.