Genetic Optimization: Living Structure

Assignment 5 Brief:

A genetic algorithm is an heuristic search that is inspired by Charles Darwin’s theory of natural evolution. This algorithm reflects the process of natural selection where the fittest individuals are selected for reproduction in order to produce offspring of the next generation. Evolutionary computation is a branch of computation that is quite unique. For one, it is not specific to any problem or task. It is a framework for solving generic problems. This offers interesting capacities for the design process where we are usually the ones iterating over a design decision in order to evaluate its effectiveness. If we could abstract the forces which guide a design decision, then we could potentially utilize evolutionary algorithms to assist us in finding optimal solutions given a number of design criteria.


The objective of this assignment is to utilize evolutionary solvers in order to optimize a design. With the help of Galapagos and Biomorpher, plugins for grasshopper, I was able to search for the most optimal solution for the architectural design. The parameters in which the design evolved around were; solar radiation, temperature, pedestrian circulation and mycelium growth.

Developed at:

IAAC, Institute for Advanced Architecture of Catalonia, during the Master for Advanced Architecture 2018/19

Project By:

Justin Sheinberg


Rodrigo Aguirre


Daniil Koshelyuk, Nikoleta Mougkasi