# An Innovative Enhanced JAYA Algorithm for the Optimization of Continuous and Discrete Problems
## 4 Results and Discussion
### Numerical Evaluation
However, it should be noted that better convergence is associated with EJAYA, as shown in Figure 2. In F4, the best fitness for the SCA, DA, GOA, MFO, PSO, CSA, JAYA, and EJAYA are 1.30543E+01, 1.16565E+01, 8.20644E+00, 3.10525E\(-\)03, 2.62136E\(-\)01, 5.23108E+00, 4.99795E+00, and 4.33560E\(-\)08, respectively. EJAYA reaches the lowest value (the best solution in minimization). In solving F5, EJAYA is again recognized as the best method, accounting for 2.33569E+01. Similarly, in F6, various algorithms can discover the best solution, but EJAYA has a faster convergence rate than the others. The comparison among F1-F6 shows that applying modifications to the JAYA algorithm can be sufficiently effective to improve its efficiency compared with its basic version and other recent algorithms. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Function** & **Algorithm** & **Mean** & **STD** & **Worst** & **Best** \\ \hline \multirow{8}{*}{F1} & SCA & 1.03246E\(-\)02 & 2.21581E\(-\)02 & 4.99561E\(-\)02 & 4.70286E\(-\)05 \\ \cline{2-6}  & DA & 7.11906E+02 & 3.98958E+02 & 1.17339E+03 & 2.35173E+02 \\ \cline{2-6}  & GOA & 4.37911E 00 & 2.77415E+00 & 8.76370E+00 & 2.02460E+00 \\ \cline{2-6}  & MFO 2.0024E+03 & 4.47089E+03 & 1.00000E+04 & 1.55478E\(-\)02 \\ \cline{2-6}  & PSO & 9.26402E\(-\)09 & 1.56966E\(-\)08 & 3.68461E\(-\)08 & 1.69501E\(-\)11 \\ \cline{2-6}  & CSA & 8.15910E\(-\)02 & 3.91503E\(-\)02 & 1.34609E\(-\)01 & 5.01376E\(-\)02 \\ \cline{2-6}  & JAYA & 1.67017E\(-\)04 & 7.75324E\(-\)05 & 2.40270E\(-\)04 & 5.68884E\(-\)05 \\ \cline{2-6}  & EJAYA & 4.51194E\(-\)52 & 5.40138E\(-\)52 & 1.33419E\(-\)51 & 4.30324E\(-\)54 \\ \hline \multirow{8}{*}{F2} & SCA & 1.66467E\(-\)05 & 2.84255E\(-\)05 & 6.62285E\(-\)05 & 3.21435E\(-\)07 \\ \cline{2-6}  & DA & 1.25115E+01 & 4.74389E+00 & 1.84707E+01 & 5.28163E+00 \\ \cline{2-6}  & GOA & 4.87563E+00 & 3.68567E+00 & 1.11171E+01 & 1.98699E+00 \\ \cline{2-6}  & MFO 8.00000E+03 & 8.36660E+03 & 2.00000E+04 & 5.23906E\(-\)03 \\ \cline{2-6}  & PSO & 5.41294E\(-\)04 & 6.34133E\(-\)04 & 1.60348E\(-\)03 & 7.37568E\(-\)06 \\ \cline{2-6}  & CSA & 3.78993E+00 & 1.64683E+00 & 5.37818E+00 & 1.57713E+00 \\ \cline{2-6}  & JAYA & 4.80091E\(-\)03 & 1.41672E\(-\)03 & 6.55615E\(-\)03 & 2.68801E\(-\)03 \\ \cline{2-6}  & EJAYA & 2.05072E\(-\)33 & 3.80692E\(-\)33 & 8.84524E\(-\)33 & 1.04480E\(-\)35 \\ \hline \multirow{8}{*}{F3} & SCA & 1.56908E\(-\)04 & 2.71951E\(-\)04 & 6.40716E\(-\)04 & 7.97609E\(-\)06 \\ \cline{2-6}  & DA & 3.16037E\(-\)05 & 5.17153E\(-\)05 & 1.20071E\(-\)04 & 1.12308E\(-\)08 \\ \cline{2-6}  & GOA & 1.52414E\(-\)01 & 3.40808E\(-\)01 & 7.62070E\(-\)01 & 3.31072E\(-\)15 \\ \cline{2-6}  & MFO 4.00000E+03 & 5.47723E+03 & 1.00001E\(+\)04 & 1.40428E\(-\)02 \\ \cline{2-6}  & PSO & 9.13802E\(-\)02 & 2.04332E\(-\)01 & 4.56901E\(-\)01 & 0.00000E+00 \\ \cline{2-6}  & CSA & 4.46483E\(-\)29 & 6.23888E\(-\)29 & 1.52669E\(-\)28 & 5.54668E\(-\)31 \\ \cline{2-6}  & JAYA & 0.00000E+00 & 0.00000E+00 & 0.00000E+00 & 0.00000E+00 \\ \cline{2-6}  & EJAYA & 0.000000E+00 & 0.00000E+00 & 0.00000E+00 & 0.00000E+00 \\ \hline \end{tabular}
\end{table} 
Table 2: The findings of F1–F6. Table 3 summarizes the findings for F7-F12. According to this table, the proposed technique is ranked as the best algorithm by determining the smallest number for the mean, standard deviation (STD), and worst and best values. Upon closer examination, EJAYA, in F7, presents the best results, accounting for 2.67151E\(-\)03. However, in F8, MFO is ranked first, followed by PSO and EJAYA. While EJAYA is not ranked as the best algorithm in F8, it outperforms basic JAYA. In the case of F9, there are various methods with outstanding performance, one of which, with quick convergence, is EJAYA. Similarly, EJAYA outperforms other algorithms in F10 and F11 due to its effective potential in discovering optimum solutions with adequate convergence. As for F12, EJAYA is placed second, while PSO obtains the best solution. Although some algorithms may have identified a superior solution in a few functions, they are not as robust as EJAYA.