Before revision:  As one particular result, we apply this method and a novel domination argument to show an exponential lower bound for the runtime of the mutation-only simple GA on \onemax for arbitrary population size.
After revision:  For the special case of algorithms using standard bit mutation with a random mutation rate (called uniform mixing in the language of hyper-heuristics), we prove the result stated by Dang and Lehre (PPSN 2016) and extend it to mutation rates other than \Theta(1/n), which includes the heavy-tailed mutation operator proposed by Doerr, Le, Makhmara, and Nguyen (GECCO 2017). We finally apply our method and a novel domination argument to show an exponential lower bound for the runtime of the mutation-only simple GA on \onemax for arbitrary population size.