Yeah, most effective genetic algorithms take a hybrid approach where they only do more dramatic mutations for some of the population, and then optimize the rest

Yeah, most effective genetic algorithms take a hybrid approach where they only do more dramatic mutations for some of the population, and then optimize the rest with a regular fitness function and small variations. The goal with these systems is to have several different but effective breeds emerge. I didn't dig into this implementation, but it seems like it doesn't carry many (more than one?) individuals between cycles.