generative-designlisted

# Generative Design for AEC Computational Design ## 1. Generative Design Paradigm ### 1.1 Definition and Scope Generative design is a computational design methodology in which a designer defines a problem through goals, constraints, and variable parameters, and an algorithmic system autonomously generates, evaluates, and evolves candidate solutions across a defined design space. Unlike traditional design where the human produces every solution manually, generative design shifts the designer's role from direct form-maker to curator of outcomes — defining *what* is desired rather than *how* to achieve it. In the AEC context, generative design applies to problems ranging from single-building floor plan layouts and structural topologies to neighborhood-scale massing studies and infrastructure routing. The common thread is a design space too large for exhaustive manual exploration. ### 1.2 Distinction from Parametric Design The confusion between parametric and generative design is pervasive. The distinction is fundamental: | Aspect | Parametric Design | Generative Design | |---|---|---| | **Core action** | Define relationships between parameters | Explore the solution space algorithmically | | **Designer's role** | Adjust sliders, observe outcomes | Define objectives and constraints, curate results | | **Output** | One solution per parameter state | Population of diverse candidate solutions | | **Search method** | Manual, intuition-driven | Automated, algorithm-driven | | *