It depends, but I don't think general statements like that are necessarily true. Most methods allow trade-offs between converging quickly on local optima vs finding global optima. The mutation aspect of genetic algorithms is just one way to do this. With well tuned mutation parameters, genetic algorithms can definitely be successful at finding global optima, but similar measures exist for most methods.