Genetic Algorithms are most commonly used when the derivative of the function is not known or incalculable. In this way, standard numerical methods cannot find optimal solutions as they are built from 'following the gradient'. Common examples of this include scheduling, finding the pareto front of multi objective problems, and reinforcement type problems for game AI design.