Project Brief:

The Genetic Optimization – Performative Facades project explores the distribution of performative geometries across single facade, while being analyze under a specific context which is the town of Rocinha in Rio de Janeiro, Brazil. 

As humidity being Rocinha biggest weather complication, the main objective of the project is to find the most performative assembly of a gradient array of single surface paneling system within a facade, while also enhancing humidity of the interior of the living spaces of the dwellers. This being derive from parameters such as radiation and wind-flow on the targeted wall. That being said, the surface geometries being explored are the panels that were selected out of range options that would suit best the chosen context due to the their current building techniques and local material accessibility within informal settlements as it is Rocinha. 

The panel parametrization such as curve opening and scalability will the best result for the maximum shading on the wall, as well as, maximum wind-flow across the whole wall. Thus, the extrapolated wall generations catalogue will provide the most efficient and accurate wall assembly for the intervention.

Pseudo Code:

This will be determining the steps taken for the entire process of optimizing the facade panels.


Defining Parameters:


Optimizing for the Solution:

By using means of optimization (using Biomorpher), we were able to obtain the most efficient solution for the facade panel based on the parameters and the conditions that had been setup.



Displaying all the generations and modules created by the optimising solver.


Performance Graph From Solver:

The performance graph extracted from the solver, of optimizing different generations and concluding with the most efficient option.

The Most Efficient Option – Breakdown


Curvature Analysis:


The Final Render:


Genetic Optimization // Optimizing Facade Panels  is a project of the Institute for Advanced Architecture of Catalonia developed at Master in Advanced Architecture in 2020/2021 by:
Student: Amandeep Singh Sasan, J.Levy Rodriguez, Ziyad Waseef
Faculty: Rodrigo Aguirre | Faculty Assistant: Ashkan Foroughi