Evolutionary Computational Design 2.0

Evolutionary Computation (EC) is a sub-field of artificial intelligence (AI) which uses the “Evolutionary Algorithm” (EAs) to solve problems that have too many variables for traditional algorithms. This method selects the best alternatives between various solutions based on problems’ criteria and constraints, known as “Optimization.” The engineering community (including architects and structural engineers) could benefit from this design method as a rapid and high-quality decision-making method and tool to increase the speed and quality of their design choice in the building design field.

After the successful first edition of the workshop, this time, participants will dive deep into how to use the EAs to study the effect of architectural design decisions on buildings’ structures’ performance and how to select optimum design alternatives among various design solutions. To achieve this goal, we use “Karamba3D” as a Finite Element (FE) analysis tool, which provides an accurate analysis of spatial trusses, frames, and shells in the early design stage, and “Galapagos” as an optimization tool based on the genetic algorithm.

They are both fully embedded in the parametric design environment of Grasshopper, a plugin for the 3D modeling tool Rhino. This makes combining parameterized geometric models, finite element calculations, and evolutionary optimization algorithms easy.