Hello everyone,
as the title says I have a question about the gene pool component in combination with an evolutionary solver such as Octopus.
I am currently working on a way to separate a building into each apartment. First having a corridor out of two connected points and then with the evaluate length component I split the outer curve into each unit. All variables are in two gene pools and then I connect them into the main Octopus multi-objective search component. The main objectives is having evenly sized apartments and for example at the same time minimum sized corridor length.
However, I am running into the problem that at each iteration every gene of every pool will be changed and therefore finding an optimum is quite random. As gene pool B is dependent on gene pool A it would be great to “lock” pool A for a couple of iterations or even a whole generation.
So in other words pool B (slave) will be changed at every iteration – but pool A (master) only at a given time when a statement is for example true OR at every x amount of iteration (therefore i would need a counter?)
Is there a way to do such thing in Octopus?
The file is pretty basic with only the main octopus component. Sadly, even after going through the provided octopus example files I couldn’t figure out how the advanced components really work.
Thank you in advance 
genepool_pointsoncurve.gh (518.7 KB)