Running Generative Design
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Studies can be run using different methods. In the Create Study window, you can choose from four different generation methods (find out more about this in the section).
An optioneering process lets you explore all possible solutions that the graph can produce. Generative Design will generate the solutions based on the constraints that were defined in the Dynamo graph.
To run an optioneering process, follow these steps:
Launch Create Study from the Generative Design menu in Dynamo.
Select a graph and select Randomize from the Method drop-down as the generation method (see the section for more information).
Under Inputs, make sure that all the desired inputs are present. For inputs that should not change on each run, uncheck the box alongside it and set the desired value.
Under Generation Settings, choose how many solutions you want to create.
Under Generation Settings, select a random seed (or number) to begin the randomization with, or use the default value.
Under Issues, resolve any items.
Finally, click Generate to run your optioneering process.
An optimization process uses the computer to evolve your design to find the most suitable options, based on the constraints and goals provided.
To run an optimization process in Generative Design, follow these steps:
Launch Create Study from the Generative Design menu in Dynamo.
Under Inputs, make sure that all of your desired inputs are present. For inputs that should not change on each run, uncheck the box alongside it and set the desired value.
Under Set goals, go through each objective and set the optimization goal you want to achieve - Maximize or Minimize.
Under Set constraints, you can optionally set a minimum and maximum for each output.
Under Generation settings, set a population size or use the default value. This represents the number of options that Generative Design will create in each generation.
Under Generation settings, can set the number of generations you want to create, or use the default value. Remember that each new generation is a range of options that falls between the two best designs from the previous generation.
Under Generation Settings, select a random seed (or number) to begin the optimization with, or use the default value.
Under Issues, resolve any items.
Finally, click Generate to run your optimization process.
Generative Design uses , an elitist multi-objective genetic algorithm to optimize results.
Select a graph and select Optimize as the generation method (see the section for more information).
