Genetic Algorithm CrossoverFraction and EliteCount

Hi everyone,

I'm currently trying to solve a binary optimization problem with the GA. I have defined my fitness and constraint function and all variables as integers with bounds [0 1]. Since GA sets a lot of options to default in this setting, there are only a few things to play with:

populationSize, CrossoverFraction, EliteCount

First question: Am I missing any options that could help my optimization?

Second question: If I am setting CrossoverFraction and EliteCount to 0 the optimization should be totally random (only mutation), but in my case the graph looks like this:

Is anyone able to explain what exactly these options do? There are some good examples in the documentation but this is contrary to my understanding.

EDIT: I attached a short script and some input data, so maybe someone is able to reproduce my problem and find any answers. Thanks in advance for your help