Generative design for architecture uses the same workflow as generative design for manufacturing, but it involves more complex goals and more stake-holders. We began our process by collecting data from employees and managers about work styles and location preferences. We then developed six primary and measurable goals: work style preference, adjacency preference, low distraction, interconnectivity, daylight, and views to the outside. We created a geometric system with multiple configurations of work neighborhoods, amenities, circulation, and even stacked private offices. Then we automated the process of exploring thousands of configurations and discovering ones that managed trade-offs and scored best.
Project Discover is a workflow for generative design for architecture. It involves the integration of a rule-based geometric system, a series of measurable goals, and a system for automatically generating, evaluating, and evolving a very large number of design options. The result is a tool to explore a wide design space, and get closer and closer to achieving all of the goals simultaneously.