“Optimized” floor plan with genetic algorithms

Genetic algorithms are inspired by natural selection, where the system is given a set of inputs and the “best” iteration is chosen until there’s some kind of convergence to a solution. Joel Simon applied this process to floor plan design.

The creative goal is to approach floor plan design solely from the perspective of optimization and without regard for convention, constructability, etc. The research goal is to see how a combination of explicit, implicit and emergent methods allow floor plans of high complexity to evolve. The floorplan is ‘grown’ from its genetic encoding using indirect methods such as graph contraction and emergent ones such as growing hallways using an ant-colony inspired algorithm.

The results were biological in appearance, intriguing in character and wildly irrational in practice. It was a fun learning experience and I plan to re-use methods in other projects.

[via kottke]