Grasshopper

algorithmic modeling for Rhino

Hello!

Thank you for your helpful tool.

I am currently running an evolutionary optimization for FRP form generation and had two quick questions. In my optimization, the genes are the geometric parameters to generate the structure shape. The objectives to optimize are the weight and the strain energy, both to be minimized.

1. My first question is then: I know it’s clearly stated that Wallacei is a multi-objective optimization, is it fair to assume it could also work for a single objective optimization? I am curious to compare where multi-objective and single-objective optimization.

2. My second question regards the validation of results before they are fed into the Wallacei component. I start with the single-objective optimization for the weight of the structure. Before a structure can be considered in the algorithm, it must verify (1) a maximum deflection criteria, (2) a minimum buckling criteria, and (3)a stress criterion (Tsai-Wu). If those 3 conditions are verified, than the design is deemed safe to be considered. I introduced this verification in the form of if statements:

    1. If the three criteria are verified, then the value of the weight inherited to Wallacei is set to the structure’s weight.
    2. If one of the three criteria was not verified, the value of the weight inherited to Wallacei is set to 100 000 (i.e a very large number). In the post-processing, the  Fitness Values can be sorted to eliminate the individuals that correspond to the 100 000 value.

The logic behind this strategy is that the optimization will drive away from those 100 000 value solutions with each generation. Is this assumption correct? Is there perhaps a different/more efficient way to validate the solutions?

Thank you for your input.

Best regards,

Mohamad Tuffaha

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