Genetic Optimization

Incisive

The task for this assignment was to utilize Evolutionary Computation in your studio or seminar projects which in my case was my Perinode F from my studio Intelligent Cities. And later to define a design task to abstract, define a solution space, and deploy Galapagos, Goat*, or Opossum* to search the solution space for the most optimal solutions.

Brief:

Firstly the existing urban fabric was taken in the form of  Breps. After that Breps were divided into two inside and outside of the region of interest i.e, the site. Then turn by turn the existing amenities were tested with each amenity having a range of households it’s catering to.The Radius is taken according to average walking distance for that particular amenity.  Then the Galapagos finds the most optimum location in the remaining buildings inside the site which do not come under the radius vicinity of the particular amenity.As the idea is to install fewer amenities but still closer to the maximum possible number of households. The colors in gradient represent the distance from the optimum location found for the new amenity where green being the closest and the red as farthest in the radius of approachability.

Process

Galapagos finding the optimum location for each amenity.

Implementation

Incisive is a project of IaaC, Institute for Advanced Architecture of Catalonia developed at Master in Advanced Architecture in 2016/2017 by:
Students: Vishesh Behl
Faculty: RODRIGO AGUIRRE & ALDO SOLLAZZO