Project scope

In relation to an urban development project, I studied the possibility of using evolutionary solver algorithm to optimize the distribution of functions and define the massing blocks based on a series of quantifiable targets:

  • Offset all Co2 produced by the nearby highway and lower the carbon footprint of the development by at least 10% per year
  • Process and ship all the goods incoming from railway cargo station onsite
  • Crate high standard homes and increase population density to reach city average
  • Create employment for all new residents + 20% extra
  • Create suitable education facilities

The algorithm was created on a fictional 2km by 2km site, based on the geometrical model selected for the real site project. The intent is to define a very flexible and customizable logic to suite various shape sites and different design options.

Functional optimization

Testing the model on the fictional square site


Testing Design options

  1. User defined plot shape

2. User option for 100% horizontal distribution

3. User option for 100% vertical distribution

Algorithm applied to existing site

Position, direction and density of blocks defined manually

1.Functional distribution

2. Schematic design of all elements

3. Resulting data management allows full customization and detail design