Alpine N.1 is a non-continuous, non-convex, and multimodal function with one global minimum at the margin of the definition range at f (0, ..., 0) = 0. Here, the model parameter space was designed in the shape of a descending mountain landscape with multiple local minima in the valleys. Unlike Ackley's function, Alpine N.1 is not differentiable and possesses a far lower density of local extrema. The EAs found the global minimum reliably in this benchmark run, even for high-dimensional parameter spaces. As expected, searches with SOPPI often ended in local minima. However, using a decreasing step length to find the best solution of the d-dimensional function improved the performance considerably.