Run simulation by picking up randomized input data

Hi,

I am using Galapagos to optimize building shape by minimizing its energy usage. Beyond the optimization, I would like to run the energy simulation using randomized input data to get random solutions. As input data, I am using multiple sliders that change the building shape. I need that these sliders are moved randomly.

Do you know if there is any plugin that allows me to pick up randomly input data for the simulation?

It should work like randomize function in the Generative Design of Revit.

I saw the Anemone plugin for looping, but I am not sure if it is suitable for picking up randomly the input data.

Do you have any advice on how to proceed?

Many thanks!

Best regards,

Julia

You can include the “seed” slider in the fitness. Won’t give you a meaningful result but you can create a complex formula driving the seed example fitness=1/(building height * seed) .

This case you can include randomized options in your optimizations.

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Let’s say you have a setup where a certain number of sliders and their ranges are the parameters and you use Galapagos. You only have to connect all relevant sliders to it as Genome and provide another Fitness value that gets minimized (towards 0) or maximized when the sliders are altered by Galapagos. The latter needs to be a number.
The simulation will find a single optimum by trying different slider value permutations, which already is kind of like randomly choosing parameters and evaluating the result by fitness.
Instead of just evaluating climate and/or building ecology data, you could also feed the building or ground plan size parameters to Galapagos.
What you won’t get is a catalogue of more or less optimized building shells. You would probably want to look into more complex tools like Wallacei for something like this.

Now, this has some pitfalls! In general genetic optimizations are only as good as the input data that they’re initialized with and you might not like the result. They follow the garbage in, garbage out principle and are highly biased, since you setup the boundary conditions that might already be flawed from the get-go.
In terms of energy usage of a building shell, you should theoretically get a perfect sphere, if you would have a setup, where it could find the “real”, “scientific” optimum. :slight_smile:

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Thank you very much for this suggestion!

Hi,

thank you very much for these suggestions.
I have not heard about Wallacei so far. Thanks!
Just my curiosity. Did you use it? Do you have a comparison with Octopus?

Best regards,

Julia

In my experience wallaceiX is better compared to octopus. Specifically with a better UI and data analysis tools.

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No, I’ve used neither of those. I usually script my stuff in Python. :wink:

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