Evolving Digital Morphogenesis by Means of Biology and Computer Science

Daniel Davis – 12 November 2009

In my undergraduate thesis (BArch Victoria University, Wellington) I developed a novel method for designing with genetic algorithms. Rather than using a genetic algorithm to seek a single ‘optimal’ design, I invented a method for identifying a range of Pareto-optimal designs. Using Java I created an application that evolved a population of design outcomes using a genetic algorithm. These outcomes were sorted into multi-dimensional Pareto-fronts that the designer could then explore using a set of sliders (video). Using this application, the designer and the computer worked synergistically to explore potentials in the design space of genetic algorithms.

I applied my Pareto-optimal genetic algorithm design method to the conversion of a warehouse in Wellington, New Zealand. Working at a range of scales, I demonstrated the method being applied to space planning, structural analysis, and the design of various stairs and chairs. My thesis was selected as one of four projects from Victoria University to attend the New Zealand Institute of Architects student design awards.

Overview of the final presentation

The five presentation panels

Panel One

The first panel

Pareto-optimal Structural Design Process

Panel Two

The second panel

Detail of second panel

A floor plan selected for homogeneity

Detail of second panel

A floor plan selected for variation

Detail of second panel

A floor plan selected double height spaces

Panel Three

The third panel

Detail of third panel

Structure selected for its constructability

Detail of third panel

Structure selected to minimise window obstruction

Detail of third panel

Structure selected for its regularity

Panel Four

The forth panel

Detail of forth panel

Stair One

Detail of forth panel

Stair Two

Detail of forth panel

Stair Three

Panel Five

The fifth panel

Detail of fifth panel

Detail of fifth panel

Detail of fifth panel