In this session, we will dive deeper into optimization and cover the four basic components of the genetic algorithm: generation, selection, crossover, and mutation. We will also review three standard parameter types we can use to control our generative models and discuss the difference between objectives and constraints when specifying our design goals.
In the hands-on demo, I’ll show you how to use Discover’s special sequence input type to solve the classic Travelling Salesman Problem. Starting with a map of cities, we will create a Grasshopper model that tests various possible routes, and then use Discover to quickly find the best possible solution.
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