Genetic Optimization //Suruc Camp
“A genetic algorithm is a 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.”
