Genetic Optimization

The objective of the assignment was to create a evolutionary solver to modify and optimize our model.

With a series of parameter biomorpher is able to combine and evolve the first model to create a series of evolutions with different parameters, which generates new models of the original family.

For X-Urban studio we are working on Mexico City, near the airport. The idea is to populate the area with new clusters that have different densities and areas so that different uses can be applied to them, such as housing, recreational, working, farming etc…

Designing by hand all the cluster take a lot of time that’s why using Biomorpher in Grasshopper and by applying the correct gnome we can create different variations of the same family depending on our needs.


The objective of this project is to create different volumes to be applied in Mexico City. Depending on the volume, area, hardness of softness of the mesh, it can be applied for different uses along the city.

The parameters start by defining some base lines witch be the base for the volume, this lines will move in X and Y.

Once the lines are stablish, a radius will be applied to create a line with the properties of a metaball, then we will change the cell size to create a mesh that can be more smooth or rough.

The structure is created by using the frame of the mesh and applied an offset.




Genetic Optimization is a project of IaaC, Institute for Advanced Architecture of Catalonia developed at Master in Advanced Architecture, in 2018/2019


Students: Ricardo Lichtle

Faculty: Rodrigo Aguirre
Student Assistants: Daniil Koshelyuk and Nikoleta Mougkasi