SEE-Segment doesn't appear to be using a selection operator. It seems to just select the HoF and apply mutation and crossover to those. It could help improve the diversity maintenance to use a selection operator such as tournament selection which would allow individuals other than just the top few to continue to contribute their genetic information to the population. I would also think that the ordering of the models should also be shuffled prior to applying crossover and mutation so that HoF[0] isn't always paired with HoF[1], etc. It should be possible that a model with high fitness be paired with a model of weak fitness.
SEE-Segment doesn't appear to be using a selection operator. It seems to just select the HoF and apply mutation and crossover to those. It could help improve the diversity maintenance to use a selection operator such as tournament selection which would allow individuals other than just the top few to continue to contribute their genetic information to the population. I would also think that the ordering of the models should also be shuffled prior to applying crossover and mutation so that HoF[0] isn't always paired with HoF[1], etc. It should be possible that a model with high fitness be paired with a model of weak fitness.