The aim of this subsection is to compare the results between cases with and without the Figure shows the minimum energy demand of the initial population over the minimum solvent demand across all six runs. In comparison to the cold start, where the molecules of the initial population are randomly generated, the warm start provides a consistently better start. The influence of the quality of the initial population on the performance of the genetic value in each generation f D max (y), along with the fluctuation observed in six independent runs, is shown. Within ten generations, all runs of the warm start converge to the same molecule hex-3-ene-1,5-diyne. In contrast, the results of the cold start display a relatively large variation. In one out of six runs, a sub-optimal candidate molecule is identified after 385 the 50th generation, which also explains the persistent fluctuation observed in the cold start until the end of the calculation. Please note that the molecule hex-3-ene-1,5-diyne contains multiple unsaturated bonds and might not be suitable for use as a solvent in practice. Overall, it can be inferred that the direct warm start, as compared to the cold start, significantly enhances the efficiency and robustness of the genetic algorithm, while maintaining comparable effectiveness.