When Does Quasi-random Work?

[10,22] presented various ways for introducing quasi-random numbers or derandomization in evolution strategies, with in some cases some spectacular claim on the fact that the proposed technique was always and for all criteria better than standard mutations. We here focus on the quasi-random trick and see to which extent this technique is efficiently, by an in-depth analysis including convergence rates, local minima, plateaus, non-asymptotic behavior and noise. We conclude to the very stable, efficient, and straightforward applicability of quasi-random numbers in continuous evolutionary algorithms.