Given the broad number of convergence criteria in which the global champion was found consistently, we focused on the coverage and speedup metrics (ESI Tables and, respectively) when selecting our generalized convergence method, as shown in Figure (error bars are shown on an alternative version of this plot in ESI Figure ). Fitting the data to a power curve, we see there is a clear trade-off between these two metrics for our convergence methods. Using the fit to extrapolate out, we recognize that even at 100% coverage, the GA still provides a substantial speedup of approximately 19.6 over a comprehensive search, verifying the benefit of GA-led searches with even relatively resource-inefficient GAs. Future work should examine convergence methods and techniques beyond those suggested here to test whether the apparent Pareto front can be broken.