## 4 Computational Evaluation and Results
There are also differences in the back-side of the optimized antenna (meanders design) when compared to the two-frequencies case. Figure 9 shows the surface current distribution of the antenna for 800, 2400, and 3500 MHz bands. As can be seen, the surface current is concentrated around the U slot for the lower band. In the upper band, the higher values are concentrated around the square patch. The current distribution in the middle band is mainly located in the feeding line and the annular patch. The influence of the ground plane meanders and slots is also shown in the figure. \begin{table}
\begin{tabular}{c c} \hline \hline
**Algorithm** & **Best Fitness** \\ \hline CRO-SL (two frequency bands) & 146.24 \\ CRO-SL (three frequency bands) & 155.03 \\ Evolutionary Algorithm & 130.05 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Comparison of the best results obtained by the proposed CRO-SL approaches and an evolutionary algorithm. Figure 8: Final antenna layout for the three-frequency bands optimization case, after the optimization process; (**a**) Front view; (**b**) Bottom view. Figure 9: _Cont_. Radiation patterns and gain values for the antenna are given in Figure 10 and Table 4. At 800 MHz, the results are similar to the basic U slot antenna, as the current distribution is mainly located around it and also, the meanders and slots in the ground plane do not affect specially in this case. For the rest of the cases, the radiation pattern differs from the basic equivalent antennas, i.e., annular patch or square patch because neither a single element is involved nor the ground plane influence is negligible. Figure 10: _Cont._  
Figure 9: Surface current distribution for the antenna obtained in the three-frequency bands optimization case. The performance of the CRO-SL algorithm in this problem is shown in Figure 11 (fitness evolution), and Figure 12 performance metrics for the different substrates of the CRO-SL. Again, the GM is the most active operator in improving the searching capabilities of the algorithm. The SAbM and the 2 Px are also important in the last stages of the algorithm, both in generating good larvae and when the inclusion of the solutions into the reef is considered. \begin{table}
\begin{tabular}{c c} \hline \hline
**Frequency (GHz)** & **Gain (dBi)** \\ \hline
0.8 & 2.734 \\
2.2 & 4.793 \\
3.5 & 8.344 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Gain (dBi) for the antenna obtained in the three-frequency bands optimization case. Figure 10: Final antenna radiation pattern; (**a**) plane E and plane H at 800 MHz; (**b**) plane E and plane H at 2.2 GHz; (**c**) plane E and plane H at 3.5 GHz. Figure 11: Evolution of the CRO-SL fitness (Equation (2)) in the three-frequency bands antenna optimization process. Figure 12: _Cont._  
Here, we have shown how we are able to optimize a multi-band microstrip textile patch antenna, with capabilities in 5G services, with the CRO-SL algorithm. The obtained device after the optimization is a robust antenna, able to operate in the three frequency bands considered (850 MHz, 2.2 GHz and 3.5 GHz), where communication services such as 5G operate. The results shown for the two-frequencies and three-frequencies cases optimization shown that we are able to obtain a small textile antenna with extremely good capabilities in the desired frequency bands.