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 main objective of this assignment is for students to utilize Evolutionary solvers in order to optimize a studio or seminar project. With the help of Galapagos (or similar) or Biomorpher, students will search for the most optimal solution (maximize, minimize, or reach a certain fitness) in the architectural environment. The result of the exercise should be a series of optimized elements which can help to drive the project forward.


The objective of the project is based on the research line SO.AR (Soft architecture ) which delves into the understanding of a material system which can passively actuate to provide ventilation and shading. The purpose of creating a structure that responds to the environment reduces the need for extra energy. The material system consists of adding graphene to the mixture of a silicon based soft robot with ethanol filling the chambers. Thus when the sun radiation hits on its surface , the soft robot would rise due to the inflation produced by the ethonol bubbles to elevate this structure





 SOFT MORPHOLOGIES//Genetic Optimization is a project of Ia

Institute for Advanced Architecture of Catalonia developed at the Master in Advanced Architecture in 2018/19 by:

Student: Deepak Mudikondan Sundaram
Tutors: Rodrigo Aguirre // Assistants: Daniil Koshelyuk, Nikoleta Mougkasi