Discussion

We have successfully created three generative algorithms with their own advantages and disadvantages. Although the results are distinct, they still relate to each other in terms of programme zoning, demographics and site conditions.

POLYGON demonstrates how a traditional grid can be transmuted into Voronoi to enhance performance and livability.

TETRIS shows that simple mathematical reduction funtion could create a dynamic skyline and a good blend of different programmes within walking distance.

XYLEM is inspired from a function in Houdini which shed light on how street network can be reconfigured and shows how algorithms devised in the previous two examples can be combined to create new urban forms.

The current design process is not without flaws. We have only used a handful of parameters to define our outcome. We could introduce more parameters such as increasing the number of programmes from 3 general categories to more specific categories such as private residence, HDB estate, civic, retail, transport nodes, and etc. Other parameters such population density in the surrounding area and demographic composition such as age groups can also be introduced to help us design with more limitations and details.

Nevertheless, the algorithms are successful in demonstrating a variety of design iterations and their capability to generate livable cities. Parameters mentioned above could simply be added into the alogorithms and their effects on the design can be quickly visualised as the algorithm adapt to data changes in real time. This rapid prototyping methodology can inspire designers by producing a variety of design options in a much shorter timeframe compared to traditional processes.

Furthermore, mathematical functions such as the Shortest Path SOP in Houdini used in XYLEM could provide a paradigm shift in the way cityscapes are designed. Intuitions of architects could be complemented with mathematical calculations to push the boundary of urban design in the future.