Generative Design

What is Generative Design?

Generative design is an iterative design process that uses algorithms to generate numerous design alternatives based on specified goals, constraints, and parameters. Rather than creating a single design solution, generative systems explore the solution space to produce options that meet defined criteria, often discovering possibilities that human designers might not consider.

The process begins with defining design objectives—perhaps maximizing daylight, minimizing structural material, or optimizing views—along with constraints like site boundaries, building codes, and budget limits. The generative algorithm then produces hundreds or thousands of design variations, each representing a different balance of the competing objectives.

Machine learning and artificial intelligence increasingly power generative design systems. These tools learn from existing designs and performance data to generate solutions that satisfy complex, multi-objective criteria. They can consider factors that are difficult to optimize manually, like pedestrian flow patterns, acoustic performance, or energy consumption.

Generative design shifts the architect's role from creator to curator. Instead of developing a single design through iteration, architects define the problem parameters and then evaluate, select, and refine from algorithmically generated options. This approach can reveal unexpected solutions and provide data-driven justification for design decisions.