 One survey of Black-Box optimizations found it outranked 31 other optimization algorithms, performing especially strong on "difficult functions" or larger dimensional search spaces.The search space dimension ranges typically between two and a few hundred.Assuming a black-box optimization scenario, where gradients are not available (or not useful) and function evaluations are the only considered cost of search, the CMA-ES method is likely to be outperformed by other methods in the following conditions