## 4 Proposed Algorithm
### Experimental Results
#### 5.3.1 Results of the JIT-RMOVRPTW
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Instance**} & \multicolumn{1}{c}{\(-\)} & \multirow{2}{*}{**NSACOWDRL**} & \multirow{2}{*}{**NSACO**} & \multirow{2}{*}{**NSGA-III**} & \multirow{2}{*}{**NSGA-II**} & \multirow{2}{*}{**MOEA/D**} \\ \cline{3-3} \cline{5-7}  & & & 0.778107 & 0.659747 & 0.482335 & 0.620586 & 0.582376 \\  & Small & 9.74E\(-\)05 & 0.000594 & 0.003465 & 0.002409 & 0.002838 \\ \cline{2-7} \multirow{2}{*}{c202} & Middle & 0.783101 & 0.685152 & 0.522198 & 0.622289 & 0.612993 \\  & 0.000137 & 0.000604 & 0.003457 & 0.004938 & 0.004171 \\ \cline{2-7} \multirow{2}{*}{c202} & Large & 0.708188 & 0.609913 & 0.404309 & 0.505273 & 0.508527 \\  & 0.000179 & 0.001238 & 0.004473 & 0.003483 & 0.005629 \\ \hline \multirow{2}{*}{c206} & Small & 0.656716 & 0.557998 & 0.487161 & 0.652318 & 0.595443 \\  & 0.000298 & 0.000589 & 0.003799 & 0.007288 & 0.004559 \\ \cline{2-7} \multirow{2}{*}{c206} & Middle & 0.635402 & 0.514251 & 0.440545 & 0.561055 & 0.550337 \\  & 0.000254 & 0.000532 & 0.009169 & 0.003729 & 0.003936 \\ \cline{2-7} \multirow{2}{*}{Large} & 0.5232 & 0.441354 & 0.345311 & 0.439341 & 0.478306 \\  & 0.000319 & 0.000555 & 0.005952 & 0.002454 & 0.003588 \\ \hline \multirow{2}{*}{rc202} & Small & 0.635634 & 0.600488 & 0.560277 & 0.576173 & 0.582909 \\  & 0.000116 & 0.000439 & 0.001576 & 0.000463 & 0.001525 \\ \cline{2-7} \multirow{2}{*}{c202} & Middle & 0.591863 & 0.535674 & 0.495836 & 0.498852 & 0.567148 \\  & 0.000324 & 0.000513 & 0.000986 & 0.001867 & 0.002845 \\ \cline{2-7} \multirow{2}{*}{Large} & 0.530264 & 0.474198 & 0.479061 & 0.556831 & 0.543224 \\  & 0.000897 & 0.000483 & 0.005019 & 0.001418 & 0.002381 \\ \hline \multirow{2}{*}{rc204} & Small & 0.630401 & 0.597802 & 0.540024 & 0.471606 & 0.611194 \\  & 0.000183 & 0.000192 & 0.00278 & 0.003056 & 0.00235 \\ \cline{2-7} \multirow{2}{*}{c204} & Middle & 0.646317 & 0.617087 & 0.557666 & 0.571228 & 0.655838 \\  & 0.000236 & 0.00045 & 0.001948 & 0.002557 & 0.002609 \\ \cline{2-7} \multirow{2}{*}{Large} & 0.607741 & 0.57318 & 0.55936 & 0.582608 & 0.559298 \\  & 0.001551 & 0.001147 & 0.003931 & 0.001271 & 0.008846 \\ \hline \multirow{2}{*}{RL} & Small & 0.551697 & 0.515265 & 0.489368 & 0.436566 & 0.512563 \\  & 0.000503 & 0.0006 & 0.001642 & 0.000742 & 0.002456 \\ \cline{2-7} \multirow{2}{*}{Middle} & 0.530147 & 0.507949 & 0.493525 & 0.383 & 0.417351 \\  & 0.000205 & 8.74E\(-\)05 & 0.00193 & 0.001007 & 0.00279 \\ \cline{2-7} \multirow{2}{*}{Large} & 0.448719 & 0.427708 & 0.406559 & 0.311904 & 0.301467 \\  & 0.000595 & 0.000319 & 0.003167 & 0.001017 & 0.001066 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Mean and variance metric values of HV indicators. To determine the differences between the algorithms on different metrics, a two-by-two comparison \(p\) value test was carried out. As shown in Figures 11-15, the \(p\) value is represented by the heatmap. The \(X\)-axis is the interference coefficient, and the \(p\) values at different interference coefficients are shown on either side of the breakpoint in the \(X\)-axis. The upper triangle of each large square is the \(p\) value for HV and the lower triangle is the \(p\) value for IGD, where \(p\) values greater than 0.05 are marked in black. The \(p\)-value plots show that the algorithms differ significantly between different instances and between different interference coefficients. NSACOWDRL is significantly better than the other algorithms, especially on the C202, C206, RL, whereas on RC202, and RC204, the performance of MOEA/D is close to that of NSACOWDRL in terms of the IGD metrics. Meanwhile, as the interference coefficient increases, the variation between algorithm performances begins to decrease on C202, C206, and RC204, whereas on RC202, RL, the variation fluctuates. Algorithm performance is affected by the combination of the instances and the interference coefficients; as the interference coefficients increase, the variation between algorithms is affected more in the RC-series instances than in the C-series.