## 5 Results and Discussion
The comparison between the traditional F/DR algorithm and the F/PER algorithm is presented in Table 2. With the exception of four cases, the results demonstrate the relevance of the F/DR strategy, as random list organization does not yield better results than the conventional algorithm. Problems P6, P13, and P19 are so complex that the F/DR algorithm cannot properly solve them because even a random organization of the list offers a 58%, 27%, and 46% probability of finding a better result, respectively. Problem P20 is excluded from this classification because, although F/PER produces a better result, it occurs in only 4% of the simulations. These findings indicate that the F/DR algorithm does not consistently produce global or near-global optimal results, despite its efficiency in local list prioritization. Analyzing the specificity of problems P6, P13, and P19 in terms of their electromagnetic compatibility matrix or demand vector does not provide a simple hypothesis that allows us to infer the fundamental challenge or restriction causing the F/DR algorithm to fail. However, in MS-FAP problems with high cell demand (e.g., P6), the F/PER algorithm outperforms the conventional one, possibly because the F strategy favors cells with a non-uniform distribution of channels [43]. As evident from Tables 3 and 4, the proposed heuristics (i.e., F/DR-k and F-DR-D-k) exhibit a high likelihood of outperforming F/DR due to the introduction of statistical diversity into priority list \(L\). In particular, the results obtained using the proposed F/DR-10 algorithm outperform those achieved with the conventional F/DR algorithm. Moreover, all assessed F/DR-D-k algorithms also surpass the performance of the conventional F/DR algorithm. When focusing solely on high-demand scenarios (i.e., P4 and P5), both F/DR-10 and F/DR-D-k strategies exhibit a high likelihood of improvement or equaling the F/DR \begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline \hline \multicolumn{2}{c}{**Conventional Approach**} & \multicolumn{2}{c}{**F/DR-10**} & \multicolumn{2}{c}{**F/DR-50**} & \multicolumn{2}{c}{**F/DR-90**} \\ \hline P1 & 239 & 259 & **251** & 69\% & 21\% & **251** & 65\% & 23\% & **254** & 11\% & 81\% & 1.2 \\ P2 & 257 & 292 & **282** & 85\% & 8\% & **283** & 92\% & 6\% & **285** & 11\% & 86\% & 1.5 \\ P3 & 426 & 448 & **438** & 92\% & 2\% & **445** & 3\% & 94\% & 452 & 0\% & 100\% & 1.9 \\ P4 & 855 & 895 & **881** & 93\% & 4\% & 904 & 0\% & 100\% & 907 & 0\% & 100\% & 8.9 \\ P5 & 1713 & 1801 & **1765** & 100\% & 0\% & 1822 & 0\% & 100\% & 1816 & 0\% & 100\% & 58.6 \\ P6 & 179 & 240 & **231** & 65\% & 12\% & **230** & 57\% & 36\% & **219** & 88\% & 10\% & 0.9 \\ P7 & 252 & 269 & **266** & 16\% & 47\% & **268** & 1\% & 92\% & **269** & 0\% & 99\% & 1.1 \\ P8 & 426 & 476 & **451** & 94\% & 2\% & **449** & 100\% & 0\% & **456** & 87\% & 8\% & 1.7 \\ P9 & 524 & 593 & **592** & 2\% & 94\% & 599 & 0\% & 100\% & **566** & 96\% & 2\% & 3.1 \\ P10 & 426 & 467 & **463** & 45\% & 39\% & **461** & 15\% & 81\% & **453** & 40\% & 49\% & 2.4 \\ P11 & 426 & 472 & **464** & 58\% & 27\% & **460** & 67\% & 29\% & **464** & 18\% & 76\% & 2.3 \\ P12 & 532 & **533** & 0\% & 80\% & **533** & 0\% & 53\% & **533** & 0\% & 81\% & 1.8 \\ P13 & 308 & 310 & **309** & 5\% & 5\% & **309** & 26\% & 38\% & **309** & 37\% & 40\% & 0.8 \\ P14 & 532 & **533** & **533** & 0\% & 12\% & **533** & 0\% & 51\% & **533** & 0\% & 80\% & 1.2 \\ P15 & 308 & 315 & **310** & 10\% & 0\% & **309** & 67\% & 0\% & **309** & 32\% & 55\% & 1.1 \\ P16 & 532 & **533** & 0\% & 10\% & **533** & 0\% & 46\% & **533** & 0\% & 87\% & 1.6 \\ P17 & 220 & 222 & **221** & 7\% & 7\% & **221** & 19\% & 33\% & **221** & 3\% & 89\% & 0.8 \\ P18 & 380 & **381** & **381** & 0\% & 10\% & **381** & 0\% & 42\% & **381** & 0\% & 84\% & 1.1 \\ P19 & 528 & 533 & **530** & 19\% & 1\% & **529** & 63\% & 20\% & **529** & 71\% & 21\% & 1.4 \\ P20 & 72 & 74 & **73** & 16\% & 8\% & **73** & 84\% & 7\% & **73** & 20\% & 54\% & 0.2 \\ \hline \hline \end{tabular}
\end{table}