GENETIC WORKFLOWS:

**EVOLUTION SOLUTIONS**

**Assignment Description :**

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 computation, and specifically Genetic Algorithms, to assist us in finding optimal solutions given a number of design criteria.

**Tasks****:**

- Define: Choose a seminar project where you will apply Evolutionary Computation. Define the problem, the variables (genomes), the fitness, and the solution space. How do you prioritize when solving for multiple objectives in a design task?
- Evolve: Evolve your design task to reach optimal solutions. Be sure to utilize the matrix technique I showed in class in order to track the evolution of your system.
- Iterate: Show how adding objectives to your design task might change the results of the optimization.

**DEFINE:**

Goal of the Master in Advanced Architecture’s Seminar** Bifurcation**, led by Professor **Mark Burry**, was to design a ten meters column using the same principles of the Gaudí column.

With the given time frame of the seminar we could not experiment with the different angles of the rotation of the columns.

By using Evolutionary Computation I would like to try different rotations of the columns to check which of the rotations give the sharp edges.

EVOLUTION SOLUTIONS – smoothest column is a project of IaaC, Institute for Advanced Architecture of Catalonia developed at Master in Advanced Architecture in 2016.

Student : Sameera chukkapalli

Faculty: Luis Fraguada, Rodrigo Aguirre