I had the same problem as you and it took me a damn while to figure out the answer to this.

You need to look at keeping the same quantity of values as a separate objective (if you only had one objective before this will make it a multi-objective GA).

So if crossover produces a combination that changes one of the value quantities then give it a score of 0 for the keeping stuff the same objective; and if it has the same value quantities then give it a score of 1. You can then score your other objectives as you have been.

As for choosing the actual crossover method, see my other answer [here](http://cs.stackexchange.com/a/37295/25708). The crossover methods I talk about at the end are all crossover methods that are specific to ordered chromosomes.