From the course: Generative Design Foundations
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Evolving design
- Like evolution in nature, the genetic algorithm relies on creating many generations of designs by following just a small set of rules. The process starts by creating an initial population of designs by randomly varying the model's input parameters. It then creates the next generation of designs by applying the following three operations: during selection, two high-performing designs are chosen from previous generation to create a new design. During crossover, the parameters of the two parent designs are randomly re-configured to create a new design. Finally, during mutation there's a small probability that some of the parameters of the new design are randomly changed. And by following this basic process, a genetic algorithm can adjust the parameters of a generative model to automatically find the best possible designs. What makes this approach especially useful is that it is not specific to any one model or any one…
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