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Community Bot
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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 herehere. The crossover methods I talk about at the end are all crossover methods that are specific to ordered chromosomes.

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. The crossover methods I talk about at the end are all crossover methods that are specific to ordered chromosomes.

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. The crossover methods I talk about at the end are all crossover methods that are specific to ordered chromosomes.

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JakeCowton
JakeCowton
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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. The crossover methods I talk about at the end are all crossover methods that are specific to ordered chromosomes.