Evolutionary computation is based on feed-back systems which prescribe and implement changes in the real world. This is a closed-loop system. Once completed, new data is recollected to build the next generation of causally oriented digital twins and evolutionary-based prescription. This feed-back produces non-linear exponential business value. This difference between new non-linear and old linear responses comes from true digital transformation.
Using that cost, speed and quality predictions of the surrogate model, to test for the effectiveness. The evolutionary lifecycle creates surrogate models to predict the fitness of those models that is used to make evolutionary decisions in creating the predictive solutions. Evolutionary computing discovers and creates solutions using less data than traditional neural networks and aggressively adapts to changes in business needs.