Sorry for the silly question, but I just wanted to be sure of what “n” exactly means in the default mutation ration (1/n). According to the primer, n is the number of variables, so if I have only two sliders as genes that can assume for instance 200 values, then my mutation rate will be set as 50% (1/2), instead of 0,5% (1/200), right?
What’s more, is “n” equivalent to the problem size in computer science? I’m asking this because, besides Deb et al. (2001) recommendation, Schlierkamp-Voosen (1993) showed that the mutation rate = 1/n (where n was the size of problem) works efficiently, so I figured they both came to the same conclusion on the topic.