Step 1 - Generative Design Framework
Design Decision 1: Room Dimensions (Volume vs. Perimeter)
- Design Variables
- Room Length (slider from 10–50)
- Room Width (slider from 10–50)
- Room Height (slider from 8–20)
- Evaluators
- Total Wall Length / Perimeter (2 × (Length + Width))
- Total Floor Area (Length × Width)
- Total Room Volume (Area × Height)
- Most Important Tradeoffs to Consider
- Usable Space vs. Construction Cost: Maximizing the floor area and total spatial volume for the user while minimizing the overall wall length/perimeter to reduce the amount of siding, framing, and drywall materials needed.
Design Decision 2: Window Sizing & Layout (Light vs. Installation Cost)
- Design Variables
- Window Height
- Window Width
- Number of Windows
- Evaluators
- Total Glazing Area (Height × Width × Number of Windows)
- Estimated Glass Cost
- Total Window Frame Length (Perimeter of windows × Number of Windows)
- Most Important Tradeoffs to Consider
- Daylight vs. Budget & Installation Time: Increasing window size and quantity improves natural light and wellness, but directly increases the material cost of the glass. Furthermore, more windows require more linear framing, which drives up thermal bridging and installation labor.
Design Decision 3: Simple Structural Grid (Openness vs. Material Volume)
- Design Variables
- Number of Columns along the X-axis
- Number of Columns along the Y-axis
- Column Radius / Thickness
- Evaluators
- Maximum Span (the open distance between columns)
- Total Number of Columns (X-axis count × Y-axis count)
- Total Concrete Volume (Cross-sectional area of columns × total columns × floor height)
- Most Important Tradeoffs to Consider
- Floor Flexibility vs. Material Cost & Dead Load: Using fewer columns creates larger spans, resulting in a more "open" and flexible floor plan. However, larger spans require much thicker, heavier columns (larger radius) to support the weight, which drastically increases the total concrete volume and material costs.
Step 2 - Generative Design Study
Objective
I was trying to find the ideal set of dimensions of length, width, and height for a single room that maximizes total floor area and overall spatial volume while minimizing the total perimeter like wall length to keep material costs low?
The model takes three distinct geometric dimension inputs to construct a 3D solid box representing a room volume. It uses a 2D rectangle to calculate baseline floor parameters and then extrudes that profile upward as a solid to dynamically model the total enclosed spatial volume.
Variables are room length, room width, room height. None of these variables are . The evaluators output are total floor area, total room volume, total perimeter.
Step 3 - Generative Design Study Results
The scatterplot displays the results of our evolutionary optimization study. I have configured the chart to map Surface Area (usable floor space) on the X-axis and Perimeter (total wall length) on the Y-axis. Additionally, the data points are color-coded based on the Total Room Volume.
As expected, increasing the floor area (moving right on the X-axis) forces the perimeter to increase (moving up on the Y-axis). However, because the solver was actively hunting for optimized shapes, the points clustered tightly along the bottom edge of that curve. These specific points represent the most efficient room geometries possible (perfect squares, or shapes very close to it), which yield the highest possible floor area and volume for the absolute minimum amount of perimeter wall material.
As a designer or project manager, I would use this visualization to make highly efficient, data-driven space planning decisions.
Because perimeter length directly correlates to construction costs (framing, drywall, insulation, siding, and labor), any point that floats higher above that bottom curve represents wasted money on an inefficiently shaped (overly elongated) room. Using this chart, I can pick a point perfectly situated on the bottom edge of the curve that hits my target total volume (indicated by the color gradient), confident that I am providing maximum usable space for the client while minimizing material costs for the contractor.
