Best practice for finding an optimum with true/false condition

I’m sure this is a question that comes up a lot, but I’m wondering how to easily incorporate a true false condition into my optimization research with WAlacei.

In my example, I have two optimisation objectives with values that I want to reduce as much as possible (surface and dimensions).
And I also have true/false conditions (0 or 1) that validate or not my analysis.

I have deliberately tripled the number of true/false conditions, so that the algorithm focuses on valid solutions.

I’m trying to figure out what the best method is to prevent the algorithms from looking for solutions where the true/false condition is not the right one:

1 - Apply a multiplier on the results of the surfaces, and dimensions that I am trying to optimize.
Example, if invalid condition surface x100…

2 - Multiplied the true/false objectives.
Example ci desous I multiplied by 3, so that the solution which seems most interesting is with true false/values of 0

3 - Generate errors of calculation of surfaces and dimensions to be optimized.
Example, if condition true false not good : Surface or dimensions = Nan

I understand that Walacei does not like to have null results. Why not?

Isn’t the optimal solution search by generations an average of the absolute values of each run?

Blue look better (average values) than green ??


you can convert the unwanted solutions into Nulll solutions and that will force Wallacei to skip them… here’s a video on how to do this:

thank you, I had understood that the Null item would prevent errors or problems in the search of the algorithm

Yes correct, but it can also be used as a way to trick Wallacei and force it to skip unwanted solutions by intentionally converting them into Null values in the definition.